lunarLander/lunarLander2Discrete.ipynb

{
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Enable this cell if using Google Collab:\n",
    "\n",
    "#!pip install box2d-py\n",
    "#!pip install gym[Box_2D]\n",
    "\n",
    "# RESTART RUNTIME AFTER INSTALLING ON GOOGLE COLLAB"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **LunarLander-v2 Discrete (maximum 1000 steps)**\n",
    "#### Double Deep-Q Neural Network (online model + target Network) similar to the Cart-Pole solution)\n",
    "\n",
    "#### The input to the network consists of 8 float values that specify the coordinates of the agent, the speed in each direction, the angle...\n",
    "#### The outputs of the network don't go through any activation function; instead of probabilities, the outputs are directly state-action values (do nothing, fire main engine, fire left engine and fire right engine)\n",
    "##### (The optimal policy involves choosing the Argmax of the output vector of the Neural Network as the action for the next step).\n",
    "##### **This environment is considered to be solved when getting an average of 200 over 100 consecutive episodes.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Imports the libraries and creates the model:\n",
    "\n",
    "\n",
    "import random\n",
    "import numpy as np\n",
    "from tensorflow import keras\n",
    "import gym\n",
    "env = gym.make('LunarLander-v2')\n",
    "model = keras.Sequential()\n",
    "model.add (keras.layers.Dense(units = 128, input_shape=(8,), activation = \"relu\"))\n",
    "model.add (keras.layers.Dense(units = 128, activation = \"relu\"))\n",
    "model.add (keras.layers.Dense(units = 32, activation = \"relu\"))\n",
    "model.add (keras.layers.Dense(units = 4))\n",
    "model.compile(optimizer=keras.optimizers.Adam(lr=0.001),loss =\"mse\")\n",
    "#print (model.summary())\n",
    "\n",
    "# At first, the two models have the same parameters; however, the static model (target network) will be updated less frequently\n",
    "\n",
    "staticModel = keras.models.clone_model( model, input_tensors=None, clone_function=None)\n",
    "#print (staticModel.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Memory Replay is carried out in this function.\n",
    "# 512 random previous experiences are \"remembered\" and processed in each step with a batch size of 128\n",
    "# This way we can prevent overfitting most recent states\n",
    "# This function has been vectorised with numpy \"Put_along_axis\" and \"Take_along_axis\" functions (see comment down below) to avoid a slow \"For loop\".\n",
    "\n",
    "def executeMemoryReplayStep(memoryPreviousStates, memoryStates, memoryARD, model, staticModel, itemsInMemory):\n",
    "    randomList = np.random.permutation(itemsInMemory) # After that number everything is 0\n",
    "    \n",
    "    memoryPreviousStates = memoryPreviousStates[randomList[:numberOfLearningFromReplaySteps]]\n",
    "    memoryStates = memoryStates[randomList[:numberOfLearningFromReplaySteps]]\n",
    "    memoryARD = memoryARD[randomList[:numberOfLearningFromReplaySteps]]\n",
    "\n",
    "    \n",
    "    \n",
    "    previousState = memoryPreviousStates\n",
    "    \n",
    "    state = memoryStates\n",
    "    \n",
    "    \n",
    "    action, reward, done = np.split(memoryARD,3,axis=1)\n",
    "    \n",
    "    action = action.astype(int)\n",
    "    \n",
    "    target = model.predict(previousState)\n",
    "    \n",
    "    # Np.put_along_axis changes the value for the action selected in \"action\" into the \"target\" array.\n",
    "    # I.e., for each row, one of the four columns are modified, these indexes (0,1,2,3) for each row appear in the \"action\" array\n",
    "    # The individual updates are those of the Q-learning algorithm: only the reward obtained if done=False=0 and the reward plus the discounted value of the next state if done=True=1\n",
    "    # However, given than now we have two networks, the online network will still use Argmax to choose the action to do in each future state but the value of such action is given by the staticModel instead.\n",
    "    # This way, with Np.Take_long_axis, we take from the staticModelPredictions those indexes that correspond to the argmax of the predictions of the onlineModel for each future state. I.e, online model chooses an action and we take that index from the predictions of the static model for each future state:\n",
    "    np.put_along_axis(target, action, (reward + (1-done)*discount*np.take_along_axis(staticModel.predict(state),np.expand_dims(np.argmax(model.predict(state), axis=1),axis=1),axis=1)), axis=1)\n",
    "    \n",
    "    \n",
    "    targetArray = np.array(target)\n",
    "    \n",
    "    model.fit(memoryPreviousStates, targetArray, epochs=1, verbose = 0, batch_size =128)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function used to soft update the static Model weights for any given Tau:\n",
    "\n",
    "def updateStaticWeights(model, staticModel,tau):\n",
    "    modelWeights = model.get_weights()\n",
    "    staticWeights = staticModel.get_weights()\n",
    "    \n",
    "    #Python broadcasting:\n",
    "    \n",
    "    for i in range (len(staticWeights)):\n",
    "     \n",
    "        staticWeights[i] = (1-tau) * staticWeights[i] + tau * modelWeights[i]\n",
    "\n",
    "        \n",
    "    staticModel.set_weights(staticWeights)\n",
    "\n",
    "\n",
    "    return model, staticModel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "STATIC WEIGHTS UPDATED\n",
      "0  Episode Reward:  -93.23026549102762 .Epsilon: 0.995\n",
      "1  Episode Reward:  -220.95275001998573 .Epsilon: 0.990025\n",
      "2  Episode Reward:  -290.7317136294014 .Epsilon: 0.985074875\n",
      "3  Episode Reward:  -296.5621649661626 .Epsilon: 0.9801495006250001\n",
      "4  Episode Reward:  -90.11528835417138 .Epsilon: 0.9752487531218751\n",
      "5  Episode Reward:  -175.6114183186067 .Epsilon: 0.9703725093562657\n",
      "6  Episode Reward:  -91.59718120957886 .Epsilon: 0.9655206468094844\n",
      "7  Episode Reward:  -162.25641585896642 .Epsilon: 0.960693043575437\n",
      "8  Episode Reward:  -178.88101159202404 .Epsilon: 0.9558895783575597\n",
      "9  Episode Reward:  -131.37768900019714 .Epsilon: 0.9511101304657719\n",
      "10  Episode Reward:  -109.01443080941493 .Epsilon: 0.946354579813443\n",
      "11  Episode Reward:  -193.06551739377267 .Epsilon: 0.9416228069143757\n",
      "12  Episode Reward:  -95.21105432967117 .Epsilon: 0.9369146928798039\n",
      "13  Episode Reward:  -232.37175769528824 .Epsilon: 0.9322301194154049\n",
      "14  Episode Reward:  -116.3234250446013 .Epsilon: 0.9275689688183278\n",
      "15  Episode Reward:  -135.62068283572017 .Epsilon: 0.9229311239742362\n",
      "16  Episode Reward:  -242.00258630848276 .Epsilon: 0.918316468354365\n",
      "17  Episode Reward:  -166.0519970932254 .Epsilon: 0.9137248860125932\n",
      "18  Episode Reward:  -282.55084142182443 .Epsilon: 0.9091562615825302\n",
      "19  Episode Reward:  -143.11442037373064 .Epsilon: 0.9046104802746175\n",
      "20  Episode Reward:  -228.94216934960363 .Epsilon: 0.9000874278732445\n",
      "21  Episode Reward:  -90.74791132009639 .Epsilon: 0.8955869907338783\n",
      "22  Episode Reward:  -157.82998023355285 .Epsilon: 0.8911090557802088\n",
      "23  Episode Reward:  -522.7585040342453 .Epsilon: 0.8866535105013078\n",
      "24  Episode Reward:  -157.54040147422035 .Epsilon: 0.8822202429488013\n",
      "25  Episode Reward:  -73.8154670497492 .Epsilon: 0.8778091417340573\n",
      "26  Episode Reward:  -66.92071000213919 .Epsilon: 0.8734200960253871\n",
      "27  Episode Reward:  -129.00857731649472 .Epsilon: 0.8690529955452602\n",
      "28  Episode Reward:  -112.64004104847542 .Epsilon: 0.8647077305675338\n",
      "29  Episode Reward:  -106.88668288461379 .Epsilon: 0.8603841919146962\n",
      "30  Episode Reward:  -130.6289466967272 .Epsilon: 0.8560822709551227\n",
      "STATIC WEIGHTS UPDATED\n",
      "31  Episode Reward:  4.082700498974731 .Epsilon: 0.851801859600347\n",
      "32  Episode Reward:  -88.71409339850493 .Epsilon: 0.8475428503023453\n",
      "33  Episode Reward:  -70.33087974893547 .Epsilon: 0.8433051360508336\n",
      "34  Episode Reward:  -156.98824001935452 .Epsilon: 0.8390886103705794\n",
      "35  Episode Reward:  -71.93126931705855 .Epsilon: 0.8348931673187264\n",
      "36  Episode Reward:  -353.2832606426673 .Epsilon: 0.8307187014821328\n",
      "37  Episode Reward:  -70.84290040300345 .Epsilon: 0.8265651079747222\n",
      "38  Episode Reward:  -108.36725758050312 .Epsilon: 0.8224322824348486\n",
      "39  Episode Reward:  -88.67649299968429 .Epsilon: 0.8183201210226743\n",
      "40  Episode Reward:  -153.9018768949924 .Epsilon: 0.8142285204175609\n",
      "41  Episode Reward:  -108.98455832219761 .Epsilon: 0.810157377815473\n",
      "42  Episode Reward:  -299.86273089757657 .Epsilon: 0.8061065909263957\n",
      "43  Episode Reward:  -103.66129759158763 .Epsilon: 0.8020760579717637\n",
      "44  Episode Reward:  -208.91794911278413 .Epsilon: 0.798065677681905\n",
      "45  Episode Reward:  -64.60865994333028 .Epsilon: 0.7940753492934954\n",
      "46  Episode Reward:  -188.24729460331264 .Epsilon: 0.7901049725470279\n",
      "47  Episode Reward:  -118.15059898002787 .Epsilon: 0.7861544476842928\n",
      "48  Episode Reward:  -50.359854851065364 .Epsilon: 0.7822236754458713\n",
      "49  Episode Reward:  -111.96194564912399 .Epsilon: 0.778312557068642\n",
      "50  Episode Reward:  -297.3772043854535 .Epsilon: 0.7744209942832988\n",
      "51  Episode Reward:  -238.67405500429345 .Epsilon: 0.7705488893118823\n",
      "52  Episode Reward:  -125.60693234265126 .Epsilon: 0.7666961448653229\n",
      "53  Episode Reward:  -85.55553421075267 .Epsilon: 0.7628626641409962\n",
      "54  Episode Reward:  -138.0745176914063 .Epsilon: 0.7590483508202912\n",
      "55  Episode Reward:  -181.6222372962679 .Epsilon: 0.7552531090661897\n",
      "56  Episode Reward:  -106.13732724956265 .Epsilon: 0.7514768435208588\n",
      "57  Episode Reward:  -76.36468323784595 .Epsilon: 0.7477194593032545\n",
      "STATIC WEIGHTS UPDATED\n",
      "58  Episode Reward:  -69.63288916797111 .Epsilon: 0.7439808620067382\n",
      "59  Episode Reward:  -60.36065317681294 .Epsilon: 0.7402609576967045\n",
      "60  Episode Reward:  -102.9082347662715 .Epsilon: 0.736559652908221\n",
      "61  Episode Reward:  -86.15887176118133 .Epsilon: 0.7328768546436799\n",
      "62  Episode Reward:  -59.13436727504983 .Epsilon: 0.7292124703704616\n",
      "63  Episode Reward:  -343.02169080899637 .Epsilon: 0.7255664080186093\n",
      "64  Episode Reward:  -153.3039934656913 .Epsilon: 0.7219385759785162\n",
      "65  Episode Reward:  -139.7202825742151 .Epsilon: 0.7183288830986236\n",
      "66  Episode Reward:  -153.94450541464704 .Epsilon: 0.7147372386831305\n",
      "67  Episode Reward:  -55.03488025603852 .Epsilon: 0.7111635524897149\n",
      "68  Episode Reward:  -123.47496520811468 .Epsilon: 0.7076077347272662\n",
      "69  Episode Reward:  -110.00740253431451 .Epsilon: 0.7040696960536299\n",
      "70  Episode Reward:  -126.88044507843135 .Epsilon: 0.7005493475733617\n",
      "71  Episode Reward:  -268.088272986274 .Epsilon: 0.697046600835495\n",
      "72  Episode Reward:  -62.96658827041638 .Epsilon: 0.6935613678313175\n",
      "73  Episode Reward:  -127.035982681803 .Epsilon: 0.6900935609921609\n",
      "74  Episode Reward:  -85.94365242246384 .Epsilon: 0.6866430931872001\n",
      "75  Episode Reward:  -121.22335935521073 .Epsilon: 0.6832098777212641\n",
      "76  Episode Reward:  -73.29481700379995 .Epsilon: 0.6797938283326578\n",
      "77  Episode Reward:  -155.1530086092192 .Epsilon: 0.6763948591909945\n",
      "78  Episode Reward:  -113.65095573725064 .Epsilon: 0.6730128848950395\n",
      "79  Episode Reward:  3.2760957471957965 .Epsilon: 0.6696478204705644\n",
      "80  Episode Reward:  -56.40901345855882 .Epsilon: 0.6662995813682115\n",
      "81  Episode Reward:  -256.1959210824292 .Epsilon: 0.6629680834613705\n",
      "STATIC WEIGHTS UPDATED\n",
      "82  Episode Reward:  -69.29916381072672 .Epsilon: 0.6596532430440636\n",
      "83  Episode Reward:  -47.24611782351495 .Epsilon: 0.6563549768288433\n",
      "84  Episode Reward:  -90.37616371951994 .Epsilon: 0.653073201944699\n",
      "85  Episode Reward:  -16.710258759274296 .Epsilon: 0.6498078359349755\n",
      "86  Episode Reward:  -81.80997119762293 .Epsilon: 0.6465587967553006\n",
      "87  Episode Reward:  -111.16744357256994 .Epsilon: 0.6433260027715241\n",
      "88  Episode Reward:  -99.38296692370739 .Epsilon: 0.6401093727576664\n",
      "89  Episode Reward:  -70.08726922513225 .Epsilon: 0.6369088258938781\n",
      "90  Episode Reward:  -89.27593395829996 .Epsilon: 0.6337242817644086\n",
      "91  Episode Reward:  -25.478407358551763 .Epsilon: 0.6305556603555866\n",
      "92  Episode Reward:  -111.73126354176651 .Epsilon: 0.6274028820538087\n",
      "93  Episode Reward:  -272.8649524229333 .Epsilon: 0.6242658676435396\n",
      "94  Episode Reward:  -155.64159518909878 .Epsilon: 0.6211445383053219\n",
      "95  Episode Reward:  -98.73216876023687 .Epsilon: 0.6180388156137953\n",
      "96  Episode Reward:  -59.837690531720256 .Epsilon: 0.6149486215357263\n",
      "97  Episode Reward:  -117.198643400955 .Epsilon: 0.6118738784280476\n",
      "98  Episode Reward:  -161.60764265202155 .Epsilon: 0.6088145090359074\n",
      "99  Episode Reward:  -99.92367066086322 .Epsilon: 0.6057704364907278\n",
      "100  Episode Reward:  -64.29814028193624 .Epsilon: 0.6027415843082742\n",
      "101  Episode Reward:  -77.69858212197678 .Epsilon: 0.5997278763867329\n",
      "102  Episode Reward:  -81.29747646753424 .Epsilon: 0.5967292370047992\n",
      "STATIC WEIGHTS UPDATED\n",
      "103  Episode Reward:  -164.09834034072566 .Epsilon: 0.5937455908197752\n",
      "104  Episode Reward:  -60.480002035207235 .Epsilon: 0.5907768628656763\n",
      "105  Episode Reward:  -248.64114098358826 .Epsilon: 0.5878229785513479\n",
      "106  Episode Reward:  -143.60411892300723 .Epsilon: 0.5848838636585911\n",
      "107  Episode Reward:  -101.23935498142968 .Epsilon: 0.5819594443402982\n",
      "108  Episode Reward:  -44.57393231283672 .Epsilon: 0.5790496471185967\n",
      "109  Episode Reward:  -75.16392019297838 .Epsilon: 0.5761543988830038\n",
      "110  Episode Reward:  -125.97058869686825 .Epsilon: 0.5732736268885887\n",
      "111  Episode Reward:  -38.15727286285569 .Epsilon: 0.5704072587541458\n",
      "112  Episode Reward:  -102.48505140312407 .Epsilon: 0.567555222460375\n",
      "113  Episode Reward:  -143.85115825809402 .Epsilon: 0.5647174463480732\n",
      "114  Episode Reward:  -309.4765095235136 .Epsilon: 0.5618938591163328\n",
      "115  Episode Reward:  -153.03795711739542 .Epsilon: 0.5590843898207511\n",
      "116  Episode Reward:  -192.80004789661774 .Epsilon: 0.5562889678716474\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "117  Episode Reward:  -124.91671871787877 .Epsilon: 0.5535075230322891\n",
      "118  Episode Reward:  -98.23904033520674 .Epsilon: 0.5507399854171277\n",
      "119  Episode Reward:  -414.462846317011 .Epsilon: 0.547986285490042\n",
      "120  Episode Reward:  -70.07441226212117 .Epsilon: 0.5452463540625918\n",
      "121  Episode Reward:  -143.10535228010838 .Epsilon: 0.5425201222922789\n",
      "122  Episode Reward:  -91.8157840495884 .Epsilon: 0.5398075216808175\n",
      "123  Episode Reward:  -124.27697167678865 .Epsilon: 0.5371084840724134\n",
      "STATIC WEIGHTS UPDATED\n",
      "124  Episode Reward:  -25.15821207875767 .Epsilon: 0.5344229416520513\n",
      "125  Episode Reward:  -123.4844318950074 .Epsilon: 0.531750826943791\n",
      "126  Episode Reward:  -123.85877780694685 .Epsilon: 0.5290920728090721\n",
      "127  Episode Reward:  -56.65319432274562 .Epsilon: 0.5264466124450268\n",
      "128  Episode Reward:  -33.40814140955139 .Epsilon: 0.5238143793828016\n",
      "129  Episode Reward:  -231.32523164901795 .Epsilon: 0.5211953074858876\n",
      "130  Episode Reward:  -115.40681782313288 .Epsilon: 0.5185893309484582\n",
      "131  Episode Reward:  -180.7778062341133 .Epsilon: 0.5159963842937159\n",
      "132  Episode Reward:  -121.80873278442839 .Epsilon: 0.5134164023722473\n",
      "133  Episode Reward:  -328.1826153206558 .Epsilon: 0.510849320360386\n",
      "134  Episode Reward:  -36.36226864634784 .Epsilon: 0.5082950737585841\n",
      "135  Episode Reward:  -360.6476970016089 .Epsilon: 0.5057535983897912\n",
      "136  Episode Reward:  -280.1062331323026 .Epsilon: 0.5032248303978422\n",
      "STATIC WEIGHTS UPDATED\n",
      "137  Episode Reward:  -78.52627693404474 .Epsilon: 0.500708706245853\n",
      "138  Episode Reward:  -211.29443323319123 .Epsilon: 0.4982051627146237\n",
      "139  Episode Reward:  -70.974717382833 .Epsilon: 0.49571413690105054\n",
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      "149  Episode Reward:  -67.35246063625219 .Epsilon: 0.47147873742168567\n",
      "150  Episode Reward:  -194.2706807615404 .Epsilon: 0.46912134373457726\n",
      "151  Episode Reward:  -85.85845605221007 .Epsilon: 0.46677573701590436\n",
      "152  Episode Reward:  -225.59132948051212 .Epsilon: 0.46444185833082485\n",
      "STATIC WEIGHTS UPDATED\n",
      "153  Episode Reward:  -83.46415589671778 .Epsilon: 0.46211964903917074\n",
      "154  Episode Reward:  -51.92794015968361 .Epsilon: 0.4598090507939749\n",
      "155  Episode Reward:  -48.09635853185145 .Epsilon: 0.457510005540005\n",
      "156  Episode Reward:  -126.95530626593572 .Epsilon: 0.45522245551230495\n",
      "157  Episode Reward:  -99.76277684454952 .Epsilon: 0.4529463432347434\n",
      "158  Episode Reward:  -449.14446877339043 .Epsilon: 0.4506816115185697\n",
      "159  Episode Reward:  -75.18429490979142 .Epsilon: 0.4484282034609769\n",
      "160  Episode Reward:  -63.04431671535292 .Epsilon: 0.446186062443672\n",
      "161  Episode Reward:  -138.98006862234374 .Epsilon: 0.4439551321314536\n",
      "162  Episode Reward:  -90.18681016924245 .Epsilon: 0.4417353564707963\n",
      "163  Episode Reward:  -222.71521774605475 .Epsilon: 0.43952667968844233\n",
      "164  Episode Reward:  -142.76274570230734 .Epsilon: 0.43732904629000013\n",
      "165  Episode Reward:  -4.0379650995695044 .Epsilon: 0.4351424010585501\n",
      "166  Episode Reward:  -122.91482429196935 .Epsilon: 0.43296668905325736\n",
      "167  Episode Reward:  -61.61714760596454 .Epsilon: 0.43080185560799106\n",
      "168  Episode Reward:  -25.81561023352674 .Epsilon: 0.4286478463299511\n",
      "169  Episode Reward:  -73.97451936238599 .Epsilon: 0.42650460709830135\n",
      "170  Episode Reward:  -86.35912772182822 .Epsilon: 0.42437208406280985\n",
      "STATIC WEIGHTS UPDATED\n",
      "171  Episode Reward:  -67.81678202414828 .Epsilon: 0.4222502236424958\n",
      "172  Episode Reward:  -131.3948447817046 .Epsilon: 0.42013897252428334\n",
      "173  Episode Reward:  -44.34158394447759 .Epsilon: 0.4180382776616619\n",
      "174  Episode Reward:  -24.766326596466698 .Epsilon: 0.4159480862733536\n",
      "175  Episode Reward:  30.497730925705355 .Epsilon: 0.41386834584198684\n",
      "176  Episode Reward:  -207.50134229021694 .Epsilon: 0.4117990041127769\n",
      "177  Episode Reward:  -37.2643680265591 .Epsilon: 0.40974000909221303\n",
      "178  Episode Reward:  27.3944911921636 .Epsilon: 0.40769130904675194\n",
      "179  Episode Reward:  102.56055334981332 .Epsilon: 0.40565285250151817\n",
      "180  Episode Reward:  -49.024916037118636 .Epsilon: 0.4036245882390106\n",
      "181  Episode Reward:  -216.83043673442194 .Epsilon: 0.4016064652978155\n",
      "STATIC WEIGHTS UPDATED\n",
      "182  Episode Reward:  -57.73623567253111 .Epsilon: 0.3995984329713264\n",
      "183  Episode Reward:  -58.890275329940174 .Epsilon: 0.3976004408064698\n",
      "184  Episode Reward:  -55.67603324005792 .Epsilon: 0.39561243860243744\n",
      "185  Episode Reward:  -218.93307731218232 .Epsilon: 0.3936343764094253\n",
      "186  Episode Reward:  -16.082949884601376 .Epsilon: 0.39166620452737816\n",
      "187  Episode Reward:  -377.45938550131655 .Epsilon: 0.3897078735047413\n",
      "188  Episode Reward:  -14.81851635911795 .Epsilon: 0.3877593341372176\n",
      "189  Episode Reward:  -42.53419682583347 .Epsilon: 0.3858205374665315\n",
      "190  Episode Reward:  46.39568393705591 .Epsilon: 0.38389143477919885\n",
      "191  Episode Reward:  -38.655398757784894 .Epsilon: 0.3819719776053028\n",
      "192  Episode Reward:  -191.25546309277038 .Epsilon: 0.3800621177172763\n",
      "193  Episode Reward:  -113.53476746418465 .Epsilon: 0.37816180712868996\n",
      "STATIC WEIGHTS UPDATED\n",
      "194  Episode Reward:  -60.31637732152257 .Epsilon: 0.37627099809304654\n",
      "195  Episode Reward:  -132.10504864060746 .Epsilon: 0.3743896431025813\n",
      "196  Episode Reward:  -43.81636340360249 .Epsilon: 0.37251769488706843\n",
      "197  Episode Reward:  -103.59218815043033 .Epsilon: 0.3706551064126331\n",
      "198  Episode Reward:  -62.00131477344383 .Epsilon: 0.36880183088056995\n",
      "199  Episode Reward:  -265.21565137237894 .Epsilon: 0.3669578217261671\n",
      "200  Episode Reward:  -45.84858781349975 .Epsilon: 0.36512303261753626\n",
      "201  Episode Reward:  -27.057591972086044 .Epsilon: 0.3632974174544486\n",
      "202  Episode Reward:  -26.608724807025 .Epsilon: 0.3614809303671764\n",
      "203  Episode Reward:  151.74702571912673 .Epsilon: 0.3596735257153405\n",
      "204  Episode Reward:  -24.374465317886802 .Epsilon: 0.3578751580867638\n",
      "STATIC WEIGHTS UPDATED\n",
      "205  Episode Reward:  -194.38369087604207 .Epsilon: 0.35608578229633\n",
      "206  Episode Reward:  -29.92936412609626 .Epsilon: 0.3543053533848483\n",
      "207  Episode Reward:  36.221800907868584 .Epsilon: 0.35253382661792404\n",
      "208  Episode Reward:  -92.83646386720807 .Epsilon: 0.3507711574848344\n",
      "209  Episode Reward:  -108.49347552773462 .Epsilon: 0.34901730169741024\n",
      "210  Episode Reward:  -199.28657952817315 .Epsilon: 0.3472722151889232\n",
      "211  Episode Reward:  -267.9168999054198 .Epsilon: 0.3455358541129786\n",
      "212  Episode Reward:  -437.231813505012 .Epsilon: 0.3438081748424137\n",
      "STATIC WEIGHTS UPDATED\n",
      "213  Episode Reward:  -70.86081831346809 .Epsilon: 0.3420891339682016\n",
      "214  Episode Reward:  -18.566936692091446 .Epsilon: 0.3403786882983606\n",
      "215  Episode Reward:  -320.9699377766593 .Epsilon: 0.3386767948568688\n",
      "216  Episode Reward:  -292.3529831054085 .Epsilon: 0.33698341088258443\n",
      "217  Episode Reward:  62.68625146580936 .Epsilon: 0.3352984938281715\n",
      "218  Episode Reward:  -118.46581658422126 .Epsilon: 0.33362200135903064\n",
      "219  Episode Reward:  41.38562834207977 .Epsilon: 0.33195389135223546\n",
      "220  Episode Reward:  -223.47600430427244 .Epsilon: 0.3302941218954743\n",
      "221  Episode Reward:  5.98250528113617 .Epsilon: 0.32864265128599696\n",
      "222  Episode Reward:  25.200219800871807 .Epsilon: 0.326999438029567\n",
      "223  Episode Reward:  -39.488298400197436 .Epsilon: 0.3253644408394192\n",
      "224  Episode Reward:  -41.54265245361053 .Epsilon: 0.3237376186352221\n",
      "STATIC WEIGHTS UPDATED\n",
      "225  Episode Reward:  -20.35839118235107 .Epsilon: 0.322118930542046\n",
      "226  Episode Reward:  -15.807299390697082 .Epsilon: 0.32050833588933575\n",
      "227  Episode Reward:  -34.30183575440873 .Epsilon: 0.31890579420988907\n",
      "228  Episode Reward:  -170.88379281129966 .Epsilon: 0.3173112652388396\n",
      "229  Episode Reward:  -33.010833743685154 .Epsilon: 0.3157247089126454\n",
      "230  Episode Reward:  -54.64742340382456 .Epsilon: 0.3141460853680822\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "231  Episode Reward:  -87.55229007488445 .Epsilon: 0.3125753549412418\n",
      "232  Episode Reward:  -684.2388412488127 .Epsilon: 0.31101247816653554\n",
      "233  Episode Reward:  -21.125123005346254 .Epsilon: 0.30945741577570285\n",
      "STATIC WEIGHTS UPDATED\n",
      "234  Episode Reward:  -121.39181491995275 .Epsilon: 0.3079101286968243\n",
      "235  Episode Reward:  -107.4637880730007 .Epsilon: 0.3063705780533402\n",
      "236  Episode Reward:  -25.44626342815367 .Epsilon: 0.30483872516307353\n",
      "237  Episode Reward:  -287.901551419147 .Epsilon: 0.3033145315372582\n",
      "238  Episode Reward:  -235.7254548033447 .Epsilon: 0.3017979588795719\n",
      "STATIC WEIGHTS UPDATED\n",
      "239  Episode Reward:  -334.85098696581395 .Epsilon: 0.30028896908517405\n",
      "240  Episode Reward:  39.385803224419845 .Epsilon: 0.2987875242397482\n",
      "241  Episode Reward:  22.17982554448581 .Epsilon: 0.29729358661854943\n",
      "242  Episode Reward:  1.3216412503364552 .Epsilon: 0.29580711868545667\n",
      "243  Episode Reward:  -8.893167216723313 .Epsilon: 0.2943280830920294\n",
      "244  Episode Reward:  -100.5192176475777 .Epsilon: 0.29285644267656924\n",
      "245  Episode Reward:  -76.49084055834666 .Epsilon: 0.2913921604631864\n",
      "246  Episode Reward:  -164.03011461661572 .Epsilon: 0.28993519966087045\n",
      "247  Episode Reward:  10.183754712238226 .Epsilon: 0.2884855236625661\n",
      "248  Episode Reward:  -166.02943032051357 .Epsilon: 0.28704309604425327\n",
      "STATIC WEIGHTS UPDATED\n",
      "249  Episode Reward:  -62.94582885828483 .Epsilon: 0.285607880564032\n",
      "250  Episode Reward:  -106.93572134015615 .Epsilon: 0.28417984116121187\n",
      "251  Episode Reward:  -234.124709060162 .Epsilon: 0.2827589419554058\n",
      "252  Episode Reward:  -136.0409654006856 .Epsilon: 0.28134514724562876\n",
      "253  Episode Reward:  14.378333485210518 .Epsilon: 0.2799384215094006\n",
      "STATIC WEIGHTS UPDATED\n",
      "254  Episode Reward:  -3.412868330957778 .Epsilon: 0.27853872940185365\n",
      "255  Episode Reward:  -56.943374765322304 .Epsilon: 0.27714603575484437\n",
      "256  Episode Reward:  23.73951017841877 .Epsilon: 0.2757603055760701\n",
      "257  Episode Reward:  -127.70664432005246 .Epsilon: 0.2743815040481898\n",
      "258  Episode Reward:  -55.205431212309314 .Epsilon: 0.2730095965279488\n",
      "STATIC WEIGHTS UPDATED\n",
      "259  Episode Reward:  83.50368285857175 .Epsilon: 0.27164454854530906\n",
      "260  Episode Reward:  36.00453812956199 .Epsilon: 0.2702863258025825\n",
      "261  Episode Reward:  -53.54472364133009 .Epsilon: 0.2689348941735696\n",
      "262  Episode Reward:  -49.374447922348885 .Epsilon: 0.26759021970270175\n",
      "STATIC WEIGHTS UPDATED\n",
      "263  Episode Reward:  -161.9863389778141 .Epsilon: 0.2662522686041882\n",
      "264  Episode Reward:  -86.22952467877086 .Epsilon: 0.2649210072611673\n",
      "265  Episode Reward:  -172.05116172991796 .Epsilon: 0.26359640222486147\n",
      "266  Episode Reward:  -100.40002025789136 .Epsilon: 0.26227842021373715\n",
      "STATIC WEIGHTS UPDATED\n",
      "267  Episode Reward:  -62.09913094978995 .Epsilon: 0.2609670281126685\n",
      "268  Episode Reward:  -50.692436194698175 .Epsilon: 0.25966219297210513\n",
      "269  Episode Reward:  50.947622055136684 .Epsilon: 0.2583638820072446\n",
      "270  Episode Reward:  -64.7698197313072 .Epsilon: 0.2570720625972084\n",
      "STATIC WEIGHTS UPDATED\n",
      "271  Episode Reward:  -132.09968922310398 .Epsilon: 0.25578670228422234\n",
      "272  Episode Reward:  -48.132105687552325 .Epsilon: 0.25450776877280124\n",
      "273  Episode Reward:  -97.61698720194967 .Epsilon: 0.2532352299289372\n",
      "274  Episode Reward:  -282.9045505062651 .Epsilon: 0.2519690537792925\n",
      "STATIC WEIGHTS UPDATED\n",
      "275  Episode Reward:  -69.82056053248068 .Epsilon: 0.2507092085103961\n",
      "276  Episode Reward:  -127.95413966294456 .Epsilon: 0.2494556624678441\n",
      "277  Episode Reward:  -62.13957562454465 .Epsilon: 0.24820838415550486\n",
      "STATIC WEIGHTS UPDATED\n",
      "278  Episode Reward:  -73.65830988154944 .Epsilon: 0.24696734223472733\n",
      "279  Episode Reward:  -72.5310607234624 .Epsilon: 0.2457325055235537\n",
      "280  Episode Reward:  -115.67142711117356 .Epsilon: 0.24450384299593592\n",
      "STATIC WEIGHTS UPDATED\n",
      "281  Episode Reward:  -83.84751022503849 .Epsilon: 0.24328132378095624\n",
      "282  Episode Reward:  -52.315251168115566 .Epsilon: 0.24206491716205145\n",
      "283  Episode Reward:  -53.179142765625876 .Epsilon: 0.2408545925762412\n",
      "284  Episode Reward:  56.995338946476835 .Epsilon: 0.23965031961336\n",
      "285  Episode Reward:  -94.80294449966482 .Epsilon: 0.2384520680152932\n",
      "STATIC WEIGHTS UPDATED\n",
      "286  Episode Reward:  -50.48175472923958 .Epsilon: 0.23725980767521673\n",
      "287  Episode Reward:  -32.0767593093778 .Epsilon: 0.23607350863684065\n",
      "288  Episode Reward:  -77.51382954613311 .Epsilon: 0.23489314109365644\n",
      "STATIC WEIGHTS UPDATED\n",
      "289  Episode Reward:  -84.59444718061827 .Epsilon: 0.23371867538818816\n",
      "290  Episode Reward:  -94.41915050028715 .Epsilon: 0.23255008201124722\n",
      "291  Episode Reward:  -121.17150907027968 .Epsilon: 0.231387331601191\n",
      "STATIC WEIGHTS UPDATED\n",
      "292  Episode Reward:  116.65632722005526 .Epsilon: 0.23023039494318503\n",
      "293  Episode Reward:  16.50148915095164 .Epsilon: 0.2290792429684691\n",
      "294  Episode Reward:  -70.88966293007665 .Epsilon: 0.22793384675362674\n",
      "295  Episode Reward:  -301.3092021985539 .Epsilon: 0.22679417751985861\n",
      "STATIC WEIGHTS UPDATED\n",
      "296  Episode Reward:  -53.81593758908375 .Epsilon: 0.22566020663225933\n",
      "297  Episode Reward:  168.20847675911185 .Epsilon: 0.22453190559909803\n",
      "298  Episode Reward:  -47.451905792238776 .Epsilon: 0.22340924607110255\n",
      "STATIC WEIGHTS UPDATED\n",
      "299  Episode Reward:  -46.726735548521404 .Epsilon: 0.22229219984074702\n",
      "300  Episode Reward:  -80.64912773444459 .Epsilon: 0.2211807388415433\n",
      "301  Episode Reward:  -70.1177580217552 .Epsilon: 0.22007483514733558\n",
      "STATIC WEIGHTS UPDATED\n",
      "302  Episode Reward:  -60.49459557642489 .Epsilon: 0.2189744609715989\n",
      "303  Episode Reward:  -47.83314531708012 .Epsilon: 0.2178795886667409\n",
      "304  Episode Reward:  -58.17944090055793 .Epsilon: 0.2167901907234072\n",
      "STATIC WEIGHTS UPDATED\n",
      "305  Episode Reward:  -73.15982301952899 .Epsilon: 0.21570623976979014\n",
      "306  Episode Reward:  80.85613300731534 .Epsilon: 0.21462770857094118\n",
      "307  Episode Reward:  -72.3589458203321 .Epsilon: 0.21355457002808648\n",
      "STATIC WEIGHTS UPDATED\n",
      "308  Episode Reward:  -65.27286232265455 .Epsilon: 0.21248679717794605\n",
      "309  Episode Reward:  -78.37602559372446 .Epsilon: 0.21142436319205632\n",
      "310  Episode Reward:  -74.257531037989 .Epsilon: 0.21036724137609603\n",
      "311  Episode Reward:  -19.4732933860313 .Epsilon: 0.20931540516921554\n",
      "STATIC WEIGHTS UPDATED\n",
      "312  Episode Reward:  -24.179371428947302 .Epsilon: 0.20826882814336947\n",
      "313  Episode Reward:  -40.634688326719 .Epsilon: 0.20722748400265262\n",
      "STATIC WEIGHTS UPDATED\n",
      "314  Episode Reward:  -73.36110133455361 .Epsilon: 0.20619134658263935\n",
      "315  Episode Reward:  -140.11576105057742 .Epsilon: 0.20516038984972615\n",
      "316  Episode Reward:  -286.4433611590283 .Epsilon: 0.2041345879004775\n",
      "317  Episode Reward:  -66.66036121599237 .Epsilon: 0.2031139149609751\n",
      "318  Episode Reward:  -68.06314821662397 .Epsilon: 0.20209834538617025\n",
      "STATIC WEIGHTS UPDATED\n",
      "319  Episode Reward:  -77.86163225951138 .Epsilon: 0.2010878536592394\n",
      "320  Episode Reward:  -53.31332065681206 .Epsilon: 0.2000824143909432\n",
      "321  Episode Reward:  -21.475710033111724 .Epsilon: 0.19908200231898848\n",
      "STATIC WEIGHTS UPDATED\n",
      "322  Episode Reward:  -9.311515336459069 .Epsilon: 0.19808659230739353\n",
      "323  Episode Reward:  -0.8140199482794088 .Epsilon: 0.19709615934585656\n",
      "324  Episode Reward:  -126.56396764124896 .Epsilon: 0.19611067854912728\n",
      "STATIC WEIGHTS UPDATED\n",
      "325  Episode Reward:  -51.41457962604016 .Epsilon: 0.19513012515638165\n",
      "326  Episode Reward:  -14.45250510111598 .Epsilon: 0.19415447453059972\n",
      "327  Episode Reward:  -374.93206204408244 .Epsilon: 0.19318370215794672\n",
      "328  Episode Reward:  -95.94725695747161 .Epsilon: 0.192217783647157\n",
      "STATIC WEIGHTS UPDATED\n",
      "329  Episode Reward:  -55.60733623669007 .Epsilon: 0.1912566947289212\n",
      "330  Episode Reward:  -77.87841743811333 .Epsilon: 0.1903004112552766\n",
      "331  Episode Reward:  26.545257571080636 .Epsilon: 0.18934890919900021\n",
      "STATIC WEIGHTS UPDATED\n",
      "332  Episode Reward:  -30.514937751239458 .Epsilon: 0.18840216465300522\n",
      "333  Episode Reward:  131.20194697016805 .Epsilon: 0.18746015382974018\n",
      "334  Episode Reward:  -72.19216513689936 .Epsilon: 0.1865228530605915\n",
      "STATIC WEIGHTS UPDATED\n",
      "335  Episode Reward:  -10.738914296170691 .Epsilon: 0.18559023879528855\n",
      "336  Episode Reward:  -105.64951143591762 .Epsilon: 0.1846622876013121\n",
      "337  Episode Reward:  19.839900190616834 .Epsilon: 0.18373897616330553\n",
      "338  Episode Reward:  -153.6391785818289 .Epsilon: 0.182820281282489\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "STATIC WEIGHTS UPDATED\n",
      "339  Episode Reward:  81.83414791800341 .Epsilon: 0.18190617987607657\n",
      "340  Episode Reward:  -147.7141388071107 .Epsilon: 0.18099664897669618\n",
      "341  Episode Reward:  -17.808617577196767 .Epsilon: 0.1800916657318127\n",
      "342  Episode Reward:  -56.066348700821074 .Epsilon: 0.17919120740315364\n",
      "343  Episode Reward:  -40.004817482668415 .Epsilon: 0.17829525136613786\n",
      "344  Episode Reward:  -84.7856152838055 .Epsilon: 0.17740377510930716\n",
      "STATIC WEIGHTS UPDATED\n",
      "345  Episode Reward:  -42.93071203073396 .Epsilon: 0.17651675623376062\n",
      "346  Episode Reward:  -97.5247899324323 .Epsilon: 0.1756341724525918\n",
      "347  Episode Reward:  -84.92879850130441 .Epsilon: 0.17475600159032884\n",
      "348  Episode Reward:  47.56536615625295 .Epsilon: 0.17388222158237718\n",
      "STATIC WEIGHTS UPDATED\n",
      "349  Episode Reward:  -70.10547410474373 .Epsilon: 0.1730128104744653\n",
      "350  Episode Reward:  38.32928530317553 .Epsilon: 0.17214774642209296\n",
      "351  Episode Reward:  52.456693148947785 .Epsilon: 0.1712870076899825\n",
      "352  Episode Reward:  -98.04625577977835 .Epsilon: 0.17043057265153258\n",
      "STATIC WEIGHTS UPDATED\n",
      "353  Episode Reward:  15.465619378928931 .Epsilon: 0.16957841978827493\n",
      "354  Episode Reward:  2.0521052269257023 .Epsilon: 0.16873052768933355\n",
      "355  Episode Reward:  -84.1273626068526 .Epsilon: 0.1678868750508869\n",
      "STATIC WEIGHTS UPDATED\n",
      "356  Episode Reward:  34.21911392093684 .Epsilon: 0.16704744067563246\n",
      "357  Episode Reward:  -33.173429023090236 .Epsilon: 0.1662122034722543\n",
      "358  Episode Reward:  -37.22613809465378 .Epsilon: 0.16538114245489302\n",
      "359  Episode Reward:  -142.7641463475963 .Epsilon: 0.16455423674261854\n",
      "360  Episode Reward:  -40.33720072903668 .Epsilon: 0.16373146555890544\n",
      "361  Episode Reward:  -14.934037005862379 .Epsilon: 0.16291280823111093\n",
      "STATIC WEIGHTS UPDATED\n",
      "362  Episode Reward:  -90.38515643148152 .Epsilon: 0.16209824418995536\n",
      "363  Episode Reward:  -38.52555306938625 .Epsilon: 0.16128775296900558\n",
      "364  Episode Reward:  -88.41152528384461 .Epsilon: 0.16048131420416054\n",
      "365  Episode Reward:  46.91856759405281 .Epsilon: 0.15967890763313974\n",
      "366  Episode Reward:  -104.18860401964987 .Epsilon: 0.15888051309497406\n",
      "STATIC WEIGHTS UPDATED\n",
      "367  Episode Reward:  147.01045177948956 .Epsilon: 0.1580861105294992\n",
      "368  Episode Reward:  -107.29737400638332 .Epsilon: 0.1572956799768517\n",
      "369  Episode Reward:  189.1164428343263 .Epsilon: 0.15650920157696743\n",
      "370  Episode Reward:  -220.3487424406727 .Epsilon: 0.1557266555690826\n",
      "371  Episode Reward:  -37.58603864451547 .Epsilon: 0.1549480222912372\n",
      "STATIC WEIGHTS UPDATED\n",
      "372  Episode Reward:  -16.995955049494736 .Epsilon: 0.15417328217978102\n",
      "373  Episode Reward:  -113.68819037071623 .Epsilon: 0.1534024157688821\n",
      "374  Episode Reward:  -52.31192082750891 .Epsilon: 0.1526354036900377\n",
      "375  Episode Reward:  -71.7897853043779 .Epsilon: 0.1518722266715875\n",
      "STATIC WEIGHTS UPDATED\n",
      "376  Episode Reward:  -41.811257981623726 .Epsilon: 0.15111286553822956\n",
      "377  Episode Reward:  -172.87443486313705 .Epsilon: 0.15035730121053842\n",
      "378  Episode Reward:  -55.653135002729606 .Epsilon: 0.14960551470448571\n",
      "379  Episode Reward:  -25.822746484891614 .Epsilon: 0.14885748713096328\n",
      "STATIC WEIGHTS UPDATED\n",
      "380  Episode Reward:  -64.78565933498484 .Epsilon: 0.14811319969530845\n",
      "381  Episode Reward:  117.70135498979538 .Epsilon: 0.1473726336968319\n",
      "STATIC WEIGHTS UPDATED\n",
      "382  Episode Reward:  -134.6143408599783 .Epsilon: 0.14663577052834775\n",
      "383  Episode Reward:  -22.5604611808932 .Epsilon: 0.14590259167570602\n",
      "384  Episode Reward:  104.219033906959 .Epsilon: 0.1451730787173275\n",
      "385  Episode Reward:  96.13993022530421 .Epsilon: 0.14444721332374086\n",
      "STATIC WEIGHTS UPDATED\n",
      "386  Episode Reward:  -46.05382247132611 .Epsilon: 0.14372497725712216\n",
      "387  Episode Reward:  -66.5556232343252 .Epsilon: 0.14300635237083656\n",
      "388  Episode Reward:  16.15982091384336 .Epsilon: 0.14229132060898236\n",
      "389  Episode Reward:  -98.31553573254045 .Epsilon: 0.14157986400593744\n",
      "390  Episode Reward:  52.67738953363426 .Epsilon: 0.14087196468590776\n",
      "STATIC WEIGHTS UPDATED\n",
      "391  Episode Reward:  -450.2589047239985 .Epsilon: 0.14016760486247823\n",
      "392  Episode Reward:  75.34966727541713 .Epsilon: 0.13946676683816583\n",
      "393  Episode Reward:  196.7004029003636 .Epsilon: 0.138769433003975\n",
      "394  Episode Reward:  -14.849498051100852 .Epsilon: 0.13807558583895513\n",
      "395  Episode Reward:  49.61033014906048 .Epsilon: 0.13738520790976036\n",
      "STATIC WEIGHTS UPDATED\n",
      "396  Episode Reward:  -124.67688591094635 .Epsilon: 0.13669828187021155\n",
      "397  Episode Reward:  -249.6904343115399 .Epsilon: 0.13601479046086049\n",
      "398  Episode Reward:  -66.54448259656961 .Epsilon: 0.1353347165085562\n",
      "399  Episode Reward:  29.025107902425788 .Epsilon: 0.1346580429260134\n",
      "400  Episode Reward:  -58.340996068716066 .Epsilon: 0.13398475271138335\n",
      "401  Episode Reward:  -26.713698879779017 .Epsilon: 0.13331482894782642\n",
      "402  Episode Reward:  212.68509973880515 .Epsilon: 0.13264825480308728\n",
      "STATIC WEIGHTS UPDATED\n",
      "403  Episode Reward:  -77.82296169212611 .Epsilon: 0.13198501352907185\n",
      "404  Episode Reward:  -64.41545868711317 .Epsilon: 0.1313250884614265\n",
      "405  Episode Reward:  266.6495952541658 .Epsilon: 0.13066846301911936\n",
      "406  Episode Reward:  -43.944322261910706 .Epsilon: 0.13001512070402377\n",
      "407  Episode Reward:  227.37189178800975 .Epsilon: 0.12936504510050365\n",
      "STATIC WEIGHTS UPDATED\n",
      "408  Episode Reward:  165.19588171340183 .Epsilon: 0.12871821987500112\n",
      "409  Episode Reward:  207.37219293730476 .Epsilon: 0.12807462877562611\n",
      "410  Episode Reward:  227.02843849941553 .Epsilon: 0.12743425563174798\n",
      "STATIC WEIGHTS UPDATED\n",
      "411  Episode Reward:  122.70150735849003 .Epsilon: 0.12679708435358925\n",
      "412  Episode Reward:  -199.92279972649163 .Epsilon: 0.1261630989318213\n",
      "413  Episode Reward:  145.67584956232002 .Epsilon: 0.1255322834371622\n",
      "414  Episode Reward:  -16.827505249051654 .Epsilon: 0.12490462201997637\n",
      "415  Episode Reward:  -105.16486601128645 .Epsilon: 0.1242800989098765\n",
      "416  Episode Reward:  -21.433925622604306 .Epsilon: 0.12365869841532712\n",
      "417  Episode Reward:  -79.5696317394086 .Epsilon: 0.12304040492325048\n",
      "418  Episode Reward:  -38.12646780680477 .Epsilon: 0.12242520289863423\n",
      "STATIC WEIGHTS UPDATED\n",
      "419  Episode Reward:  83.86839183719094 .Epsilon: 0.12181307688414106\n",
      "420  Episode Reward:  -35.39644207748378 .Epsilon: 0.12120401149972035\n",
      "421  Episode Reward:  -76.90466816960961 .Epsilon: 0.12059799144222175\n",
      "422  Episode Reward:  101.84119173712702 .Epsilon: 0.11999500148501063\n",
      "423  Episode Reward:  206.36616892659148 .Epsilon: 0.11939502647758558\n",
      "STATIC WEIGHTS UPDATED\n",
      "424  Episode Reward:  204.16543893460064 .Epsilon: 0.11879805134519765\n",
      "425  Episode Reward:  204.57319425469638 .Epsilon: 0.11820406108847166\n",
      "426  Episode Reward:  -28.638615176452333 .Epsilon: 0.1176130407830293\n",
      "427  Episode Reward:  212.64430098439567 .Epsilon: 0.11702497557911415\n",
      "428  Episode Reward:  -97.67266692248657 .Epsilon: 0.11643985070121858\n",
      "429  Episode Reward:  69.75883319705412 .Epsilon: 0.11585765144771248\n",
      "430  Episode Reward:  -385.7441715691212 .Epsilon: 0.11527836319047392\n",
      "STATIC WEIGHTS UPDATED\n",
      "431  Episode Reward:  186.129182128059 .Epsilon: 0.11470197137452155\n",
      "432  Episode Reward:  -9.199236417711887 .Epsilon: 0.11412846151764894\n",
      "433  Episode Reward:  5.743521965490174 .Epsilon: 0.1135578192100607\n",
      "434  Episode Reward:  -112.0839237763876 .Epsilon: 0.11299003011401039\n",
      "435  Episode Reward:  113.51252834017214 .Epsilon: 0.11242507996344034\n",
      "STATIC WEIGHTS UPDATED\n",
      "436  Episode Reward:  246.82861685881147 .Epsilon: 0.11186295456362313\n",
      "437  Episode Reward:  -40.24424186531248 .Epsilon: 0.11130363979080501\n",
      "438  Episode Reward:  -43.443757722968925 .Epsilon: 0.11074712159185099\n",
      "439  Episode Reward:  83.57393167383253 .Epsilon: 0.11019338598389174\n",
      "440  Episode Reward:  -126.63361111496882 .Epsilon: 0.10964241905397228\n",
      "441  Episode Reward:  -84.27332219564968 .Epsilon: 0.10909420695870241\n",
      "442  Episode Reward:  15.120621004926988 .Epsilon: 0.1085487359239089\n",
      "STATIC WEIGHTS UPDATED\n",
      "443  Episode Reward:  -353.4808077182439 .Epsilon: 0.10800599224428936\n",
      "444  Episode Reward:  -0.5346764850297774 .Epsilon: 0.10746596228306791\n",
      "445  Episode Reward:  -29.56979044008095 .Epsilon: 0.10692863247165257\n",
      "446  Episode Reward:  -24.011834354726503 .Epsilon: 0.1063939893092943\n",
      "447  Episode Reward:  222.5962630272135 .Epsilon: 0.10586201936274783\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "448  Episode Reward:  -19.697623271889952 .Epsilon: 0.10533270926593409\n",
      "449  Episode Reward:  -5.140435499063258 .Epsilon: 0.10480604571960442\n",
      "450  Episode Reward:  24.395129144278314 .Epsilon: 0.1042820154910064\n",
      "451  Episode Reward:  164.63317212183668 .Epsilon: 0.10376060541355137\n",
      "STATIC WEIGHTS UPDATED\n",
      "452  Episode Reward:  243.56377216765378 .Epsilon: 0.1032418023864836\n",
      "453  Episode Reward:  141.02323121829983 .Epsilon: 0.10272559337455119\n",
      "454  Episode Reward:  107.46755434732277 .Epsilon: 0.10221196540767843\n",
      "455  Episode Reward:  -44.668661739359834 .Epsilon: 0.10170090558064004\n",
      "456  Episode Reward:  229.7828340834984 .Epsilon: 0.10119240105273684\n",
      "STATIC WEIGHTS UPDATED\n",
      "457  Episode Reward:  -219.99003509359727 .Epsilon: 0.10068643904747315\n",
      "458  Episode Reward:  -66.51808033556844 .Epsilon: 0.10018300685223579\n",
      "459  Episode Reward:  -455.76633842750596 .Epsilon: 0.1\n",
      "460  Episode Reward:  -25.733496907670794 .Epsilon: 0.1\n",
      "461  Episode Reward:  -111.2953390503812 .Epsilon: 0.1\n",
      "462  Episode Reward:  22.17344191306786 .Epsilon: 0.1\n",
      "463  Episode Reward:  166.83844859418258 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "464  Episode Reward:  -158.38910772013895 .Epsilon: 0.1\n",
      "465  Episode Reward:  -316.1125674652578 .Epsilon: 0.1\n",
      "466  Episode Reward:  -58.94720267602156 .Epsilon: 0.1\n",
      "467  Episode Reward:  251.6243690402161 .Epsilon: 0.1\n",
      "468  Episode Reward:  8.71662770689889 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "469  Episode Reward:  244.65123376045912 .Epsilon: 0.1\n",
      "470  Episode Reward:  248.59342211546883 .Epsilon: 0.1\n",
      "471  Episode Reward:  -182.45786885631196 .Epsilon: 0.1\n",
      "472  Episode Reward:  202.90305943751162 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "473  Episode Reward:  89.10177738817042 .Epsilon: 0.1\n",
      "474  Episode Reward:  188.00472297711184 .Epsilon: 0.1\n",
      "475  Episode Reward:  255.61945130527513 .Epsilon: 0.1\n",
      "476  Episode Reward:  240.16313687287206 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "477  Episode Reward:  -123.12305821117266 .Epsilon: 0.1\n",
      "478  Episode Reward:  -31.12301958081754 .Epsilon: 0.1\n",
      "479  Episode Reward:  261.9670719093743 .Epsilon: 0.1\n",
      "480  Episode Reward:  202.44808990119506 .Epsilon: 0.1\n",
      "481  Episode Reward:  -80.44228576895443 .Epsilon: 0.1\n",
      "482  Episode Reward:  229.99239926026843 .Epsilon: 0.1\n",
      "483  Episode Reward:  224.4460444910451 .Epsilon: 0.1\n",
      "484  Episode Reward:  -11.475754995404387 .Epsilon: 0.1\n",
      "485  Episode Reward:  267.4015449271514 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "486  Episode Reward:  227.9608728228991 .Epsilon: 0.1\n",
      "487  Episode Reward:  249.36751959188848 .Epsilon: 0.1\n",
      "488  Episode Reward:  65.99353002056075 .Epsilon: 0.1\n",
      "489  Episode Reward:  -7.61854561468499 .Epsilon: 0.1\n",
      "490  Episode Reward:  -52.55085869986228 .Epsilon: 0.1\n",
      "491  Episode Reward:  13.310630610199027 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "492  Episode Reward:  215.0958575658641 .Epsilon: 0.1\n",
      "493  Episode Reward:  21.76021643720064 .Epsilon: 0.1\n",
      "494  Episode Reward:  7.340278191215873 .Epsilon: 0.1\n",
      "495  Episode Reward:  259.56554205704276 .Epsilon: 0.1\n",
      "496  Episode Reward:  -377.0895901783963 .Epsilon: 0.1\n",
      "497  Episode Reward:  246.54349250923153 .Epsilon: 0.1\n",
      "498  Episode Reward:  7.674983843311892 .Epsilon: 0.1\n",
      "499  Episode Reward:  -0.6203598987702748 .Epsilon: 0.1\n"
     ]
    }
   ],
   "source": [
    "numberEpisodes = 500\n",
    "\n",
    "discount = 0.99\n",
    "counter = 0\n",
    "epsilon = 1\n",
    "epsilonDecay = 0.995\n",
    "rewards = []\n",
    "tau = 0.5\n",
    "memorySize = 50000\n",
    "memoryPreviousStates = np.zeros((memorySize,8))\n",
    "memoryStates = np.zeros((memorySize,8))\n",
    "memoryARD = np.zeros((memorySize,3))\n",
    "numberOfLearningFromReplaySteps = 512\n",
    "itemsInMemory = 0\n",
    "initialiseReplayAfter = 1000 \n",
    "\n",
    "for episode in range (numberEpisodes):\n",
    "    epsilon = max (epsilon*epsilonDecay, 0.1)\n",
    "    \n",
    "    \n",
    "    done = False\n",
    "    prevObs = env.reset()\n",
    "    \n",
    "    episodeReward = 0\n",
    "    for step in range (2000):\n",
    "        if done:\n",
    "            break\n",
    "        #env.render()\n",
    "        \n",
    "\n",
    "        target = model.predict(np.expand_dims(prevObs, axis = 0))[0]\n",
    "        if (random.random()<epsilon):\n",
    "            action = random.choice([0,1,2,3 ])\n",
    "        else:\n",
    "            action = np.argmax(target)\n",
    "        \n",
    "        obs, reward, done, _ = env.step (action)\n",
    "\n",
    "\n",
    "        memoryPreviousStates[counter] = prevObs\n",
    "        memoryStates[counter] = obs\n",
    "        \n",
    "        memoryARD[counter] = [float(action), reward, float (done)]\n",
    "        \n",
    "        if (counter % 3000 == 0):\n",
    "            model.save_weights(\"lunarweights.h5\")\n",
    "            model, staticModel = updateStaticWeights(model, staticModel,tau)\n",
    "            print (\"STATIC WEIGHTS UPDATED\")\n",
    "        \n",
    "        if (itemsInMemory < (counter+1)):\n",
    "            itemsInMemory = min ((itemsInMemory+1), memorySize)\n",
    "        if (itemsInMemory >= initialiseReplayAfter):\n",
    "            executeMemoryReplayStep(memoryPreviousStates, memoryStates, memoryARD, model, staticModel, itemsInMemory)\n",
    "\n",
    "\n",
    "        prevObs = obs\n",
    "        episodeReward += reward\n",
    "        counter = (counter + 1) % memorySize\n",
    "    print (episode, \" Episode Reward: \", episodeReward, \".Epsilon:\", epsilon)\n",
    "    rewards.append(episodeReward)\n",
    "\n",
    "env.close()\n",
    "model.save_weights(\"lunarweights.h5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.plot (list(range(len(rewards))), rewards)\n",
    "plt.title(\"Rewards obtained along the learning process\")\n",
    "plt.xlabel(\"Episode number\")\n",
    "plt.ylabel(\"Reward obtained\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's train the agent for longer:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "500  Episode Reward:  -109.79763766142601 .Epsilon: 0.1\n",
      "501  Episode Reward:  -0.6926218970971547 .Epsilon: 0.1\n",
      "502  Episode Reward:  239.9192870660363 .Epsilon: 0.1\n",
      "503  Episode Reward:  -22.132765801565355 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "504  Episode Reward:  -8.446257067771166 .Epsilon: 0.1\n",
      "505  Episode Reward:  -88.91849606880584 .Epsilon: 0.1\n",
      "506  Episode Reward:  20.67406663073764 .Epsilon: 0.1\n",
      "507  Episode Reward:  -42.84748583129691 .Epsilon: 0.1\n",
      "508  Episode Reward:  259.9588067143078 .Epsilon: 0.1\n",
      "509  Episode Reward:  234.42994361026857 .Epsilon: 0.1\n",
      "510  Episode Reward:  238.40671380337676 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "511  Episode Reward:  245.3760716081011 .Epsilon: 0.1\n",
      "512  Episode Reward:  261.0793620544932 .Epsilon: 0.1\n",
      "513  Episode Reward:  229.80589505140375 .Epsilon: 0.1\n",
      "514  Episode Reward:  -41.89311042831295 .Epsilon: 0.1\n",
      "515  Episode Reward:  241.81033674671897 .Epsilon: 0.1\n",
      "516  Episode Reward:  6.835509889603273 .Epsilon: 0.1\n",
      "517  Episode Reward:  203.6486361095257 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "518  Episode Reward:  238.97552847177647 .Epsilon: 0.1\n",
      "519  Episode Reward:  227.34949030839744 .Epsilon: 0.1\n",
      "520  Episode Reward:  229.14830865491953 .Epsilon: 0.1\n",
      "521  Episode Reward:  -31.830218642655524 .Epsilon: 0.1\n",
      "522  Episode Reward:  250.4745872124888 .Epsilon: 0.1\n",
      "523  Episode Reward:  -261.12206949705626 .Epsilon: 0.1\n",
      "524  Episode Reward:  274.734472040211 .Epsilon: 0.1\n",
      "525  Episode Reward:  -72.83995517104123 .Epsilon: 0.1\n",
      "526  Episode Reward:  -328.85032763228327 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "527  Episode Reward:  267.75112550046606 .Epsilon: 0.1\n",
      "528  Episode Reward:  262.62194463453267 .Epsilon: 0.1\n",
      "529  Episode Reward:  247.64174179705924 .Epsilon: 0.1\n",
      "530  Episode Reward:  242.29155200241632 .Epsilon: 0.1\n",
      "531  Episode Reward:  251.2370950861702 .Epsilon: 0.1\n",
      "532  Episode Reward:  232.12090160934198 .Epsilon: 0.1\n",
      "533  Episode Reward:  230.99643666363332 .Epsilon: 0.1\n",
      "534  Episode Reward:  -11.545185681588961 .Epsilon: 0.1\n",
      "535  Episode Reward:  259.54375982177123 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "536  Episode Reward:  258.93462171484373 .Epsilon: 0.1\n",
      "537  Episode Reward:  227.67437424612314 .Epsilon: 0.1\n",
      "538  Episode Reward:  -7.514587989016988 .Epsilon: 0.1\n",
      "539  Episode Reward:  -27.74945450207315 .Epsilon: 0.1\n",
      "540  Episode Reward:  -126.64730827112726 .Epsilon: 0.1\n",
      "541  Episode Reward:  246.87340033384854 .Epsilon: 0.1\n",
      "542  Episode Reward:  -121.03465350053635 .Epsilon: 0.1\n",
      "543  Episode Reward:  255.1506260165442 .Epsilon: 0.1\n",
      "544  Episode Reward:  271.59967945700487 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "545  Episode Reward:  29.210113890221663 .Epsilon: 0.1\n",
      "546  Episode Reward:  225.43860412042557 .Epsilon: 0.1\n",
      "547  Episode Reward:  -254.85803861171942 .Epsilon: 0.1\n",
      "548  Episode Reward:  -356.74697961107466 .Epsilon: 0.1\n",
      "549  Episode Reward:  261.3360172048191 .Epsilon: 0.1\n",
      "550  Episode Reward:  246.085926796079 .Epsilon: 0.1\n",
      "551  Episode Reward:  -35.77343571356947 .Epsilon: 0.1\n",
      "552  Episode Reward:  242.62890752075444 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "553  Episode Reward:  247.2000615342723 .Epsilon: 0.1\n",
      "554  Episode Reward:  226.95894263303686 .Epsilon: 0.1\n",
      "555  Episode Reward:  44.8722953758093 .Epsilon: 0.1\n",
      "556  Episode Reward:  -105.04414894732288 .Epsilon: 0.1\n",
      "557  Episode Reward:  -232.20670518367766 .Epsilon: 0.1\n",
      "558  Episode Reward:  248.0070216799632 .Epsilon: 0.1\n",
      "559  Episode Reward:  -12.786718038252602 .Epsilon: 0.1\n",
      "560  Episode Reward:  237.13623943195893 .Epsilon: 0.1\n",
      "561  Episode Reward:  -70.66940306423099 .Epsilon: 0.1\n",
      "562  Episode Reward:  3.448280494198457 .Epsilon: 0.1\n",
      "563  Episode Reward:  -5.235639900535759 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "564  Episode Reward:  273.5966780182648 .Epsilon: 0.1\n",
      "565  Episode Reward:  -256.5790200914903 .Epsilon: 0.1\n",
      "566  Episode Reward:  -314.11608777717964 .Epsilon: 0.1\n",
      "567  Episode Reward:  24.157720990758676 .Epsilon: 0.1\n",
      "568  Episode Reward:  24.278544371230467 .Epsilon: 0.1\n",
      "569  Episode Reward:  14.554861497356256 .Epsilon: 0.1\n",
      "570  Episode Reward:  243.67452245740293 .Epsilon: 0.1\n",
      "571  Episode Reward:  22.076490280730553 .Epsilon: 0.1\n",
      "572  Episode Reward:  232.6214521061465 .Epsilon: 0.1\n",
      "573  Episode Reward:  257.2967833163304 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "574  Episode Reward:  -73.39662371735412 .Epsilon: 0.1\n",
      "575  Episode Reward:  28.16525114051953 .Epsilon: 0.1\n",
      "576  Episode Reward:  -54.46935438370723 .Epsilon: 0.1\n",
      "577  Episode Reward:  -32.55296869923309 .Epsilon: 0.1\n",
      "578  Episode Reward:  225.8379890207058 .Epsilon: 0.1\n",
      "579  Episode Reward:  -19.844012839461598 .Epsilon: 0.1\n",
      "580  Episode Reward:  -279.5675668223405 .Epsilon: 0.1\n",
      "581  Episode Reward:  -13.195341912054303 .Epsilon: 0.1\n",
      "582  Episode Reward:  -295.3445835732558 .Epsilon: 0.1\n",
      "583  Episode Reward:  270.8046838531982 .Epsilon: 0.1\n",
      "584  Episode Reward:  302.9828501149852 .Epsilon: 0.1\n",
      "585  Episode Reward:  -13.552243050224376 .Epsilon: 0.1\n",
      "586  Episode Reward:  237.2955110115464 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "587  Episode Reward:  14.741264278050195 .Epsilon: 0.1\n",
      "588  Episode Reward:  260.45446142144044 .Epsilon: 0.1\n",
      "589  Episode Reward:  243.72898299825764 .Epsilon: 0.1\n",
      "590  Episode Reward:  249.48685619167256 .Epsilon: 0.1\n",
      "591  Episode Reward:  270.69498223525784 .Epsilon: 0.1\n",
      "592  Episode Reward:  233.3501111526397 .Epsilon: 0.1\n",
      "593  Episode Reward:  254.5102451491826 .Epsilon: 0.1\n",
      "594  Episode Reward:  257.1129660214376 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "595  Episode Reward:  178.88193383760427 .Epsilon: 0.1\n",
      "596  Episode Reward:  262.00978428933695 .Epsilon: 0.1\n",
      "597  Episode Reward:  10.351473007825362 .Epsilon: 0.1\n",
      "598  Episode Reward:  8.04376394812138 .Epsilon: 0.1\n",
      "599  Episode Reward:  -10.595573047708129 .Epsilon: 0.1\n",
      "600  Episode Reward:  285.5654825905608 .Epsilon: 0.1\n",
      "601  Episode Reward:  220.2831344496929 .Epsilon: 0.1\n",
      "602  Episode Reward:  -148.13986457751568 .Epsilon: 0.1\n",
      "603  Episode Reward:  38.784861372530855 .Epsilon: 0.1\n",
      "604  Episode Reward:  239.27573568107132 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "605  Episode Reward:  250.2638646913182 .Epsilon: 0.1\n",
      "606  Episode Reward:  254.47343552500263 .Epsilon: 0.1\n",
      "607  Episode Reward:  -26.022647401918107 .Epsilon: 0.1\n",
      "608  Episode Reward:  46.10189074152518 .Epsilon: 0.1\n",
      "609  Episode Reward:  -1.6715109786160554 .Epsilon: 0.1\n",
      "610  Episode Reward:  252.89189466460712 .Epsilon: 0.1\n",
      "611  Episode Reward:  243.1670274916191 .Epsilon: 0.1\n",
      "612  Episode Reward:  39.370066140337855 .Epsilon: 0.1\n",
      "613  Episode Reward:  249.24861775610148 .Epsilon: 0.1\n",
      "614  Episode Reward:  263.70473417830317 .Epsilon: 0.1\n",
      "615  Episode Reward:  -51.79903838102426 .Epsilon: 0.1\n",
      "616  Episode Reward:  264.7805284353718 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "617  Episode Reward:  248.11655730046624 .Epsilon: 0.1\n",
      "618  Episode Reward:  250.66917238611958 .Epsilon: 0.1\n",
      "619  Episode Reward:  4.1674005415050885 .Epsilon: 0.1\n",
      "620  Episode Reward:  252.23809304667228 .Epsilon: 0.1\n",
      "621  Episode Reward:  200.54825359405908 .Epsilon: 0.1\n",
      "622  Episode Reward:  0.05549962909040573 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "623  Episode Reward:  262.5400072526312 .Epsilon: 0.1\n",
      "624  Episode Reward:  25.681064590421144 .Epsilon: 0.1\n",
      "625  Episode Reward:  268.23947058772995 .Epsilon: 0.1\n",
      "626  Episode Reward:  13.1361018366174 .Epsilon: 0.1\n",
      "627  Episode Reward:  269.5705132773195 .Epsilon: 0.1\n",
      "628  Episode Reward:  266.58732709126207 .Epsilon: 0.1\n",
      "629  Episode Reward:  255.79644762559343 .Epsilon: 0.1\n",
      "630  Episode Reward:  246.76224907843385 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "631  Episode Reward:  220.67382526438615 .Epsilon: 0.1\n",
      "632  Episode Reward:  8.575873474403025 .Epsilon: 0.1\n",
      "633  Episode Reward:  -230.98760412601126 .Epsilon: 0.1\n",
      "634  Episode Reward:  -246.93654651677943 .Epsilon: 0.1\n",
      "635  Episode Reward:  8.352489942694078 .Epsilon: 0.1\n",
      "636  Episode Reward:  54.613598520560004 .Epsilon: 0.1\n",
      "637  Episode Reward:  -5.736358581928101 .Epsilon: 0.1\n",
      "638  Episode Reward:  245.3582352039478 .Epsilon: 0.1\n",
      "639  Episode Reward:  254.20867599798294 .Epsilon: 0.1\n",
      "640  Episode Reward:  -165.0301009473292 .Epsilon: 0.1\n",
      "641  Episode Reward:  284.8459130760189 .Epsilon: 0.1\n",
      "642  Episode Reward:  253.13179200432666 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "643  Episode Reward:  236.96234625383906 .Epsilon: 0.1\n",
      "644  Episode Reward:  -249.44614700032085 .Epsilon: 0.1\n",
      "645  Episode Reward:  290.835647312998 .Epsilon: 0.1\n",
      "646  Episode Reward:  -18.41894367170093 .Epsilon: 0.1\n",
      "647  Episode Reward:  244.4553670409381 .Epsilon: 0.1\n",
      "648  Episode Reward:  -42.97626322194949 .Epsilon: 0.1\n",
      "649  Episode Reward:  -255.1316086101092 .Epsilon: 0.1\n",
      "650  Episode Reward:  49.31742744704417 .Epsilon: 0.1\n",
      "651  Episode Reward:  167.23524328003765 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "652  Episode Reward:  271.17711681326625 .Epsilon: 0.1\n",
      "653  Episode Reward:  9.439882865372923 .Epsilon: 0.1\n",
      "654  Episode Reward:  264.30633626351266 .Epsilon: 0.1\n",
      "655  Episode Reward:  68.52630632537995 .Epsilon: 0.1\n",
      "656  Episode Reward:  237.25402461649907 .Epsilon: 0.1\n",
      "657  Episode Reward:  -2.190529396760013 .Epsilon: 0.1\n",
      "658  Episode Reward:  -203.49290176040842 .Epsilon: 0.1\n",
      "659  Episode Reward:  167.46218122712588 .Epsilon: 0.1\n",
      "660  Episode Reward:  242.90398539820134 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "661  Episode Reward:  40.554207440562294 .Epsilon: 0.1\n",
      "662  Episode Reward:  278.75482111630697 .Epsilon: 0.1\n",
      "663  Episode Reward:  310.5172991081322 .Epsilon: 0.1\n",
      "664  Episode Reward:  227.05509115437383 .Epsilon: 0.1\n",
      "665  Episode Reward:  20.449330168947498 .Epsilon: 0.1\n",
      "666  Episode Reward:  250.720516342279 .Epsilon: 0.1\n",
      "667  Episode Reward:  253.83132798003925 .Epsilon: 0.1\n",
      "668  Episode Reward:  25.8596027067629 .Epsilon: 0.1\n",
      "669  Episode Reward:  265.2211486752942 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "670  Episode Reward:  -488.8997034809004 .Epsilon: 0.1\n",
      "671  Episode Reward:  -335.6338444584753 .Epsilon: 0.1\n",
      "672  Episode Reward:  -367.8997063970141 .Epsilon: 0.1\n",
      "673  Episode Reward:  243.51040722826585 .Epsilon: 0.1\n",
      "674  Episode Reward:  238.01387717222877 .Epsilon: 0.1\n",
      "675  Episode Reward:  255.81273797903222 .Epsilon: 0.1\n",
      "676  Episode Reward:  285.57759769912354 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "677  Episode Reward:  -47.227203029506896 .Epsilon: 0.1\n",
      "678  Episode Reward:  241.6940942441662 .Epsilon: 0.1\n",
      "679  Episode Reward:  257.0940817995198 .Epsilon: 0.1\n",
      "680  Episode Reward:  -50.18623299639849 .Epsilon: 0.1\n",
      "681  Episode Reward:  -231.9471353097251 .Epsilon: 0.1\n",
      "682  Episode Reward:  259.33005664872405 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "683  Episode Reward:  107.31302078348446 .Epsilon: 0.1\n",
      "684  Episode Reward:  268.1549153085605 .Epsilon: 0.1\n",
      "685  Episode Reward:  -310.1751016920168 .Epsilon: 0.1\n",
      "686  Episode Reward:  245.31521499913094 .Epsilon: 0.1\n",
      "687  Episode Reward:  232.3908350459417 .Epsilon: 0.1\n",
      "688  Episode Reward:  285.8686302051997 .Epsilon: 0.1\n",
      "689  Episode Reward:  256.80730114033634 .Epsilon: 0.1\n",
      "690  Episode Reward:  235.04107817292328 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "691  Episode Reward:  240.22617218596758 .Epsilon: 0.1\n",
      "692  Episode Reward:  254.59385918226022 .Epsilon: 0.1\n",
      "693  Episode Reward:  235.0569198823721 .Epsilon: 0.1\n",
      "694  Episode Reward:  269.23147112566284 .Epsilon: 0.1\n",
      "695  Episode Reward:  -50.569923310245386 .Epsilon: 0.1\n",
      "696  Episode Reward:  -189.68720132503512 .Epsilon: 0.1\n",
      "697  Episode Reward:  16.144770894323443 .Epsilon: 0.1\n",
      "698  Episode Reward:  6.190920298581034 .Epsilon: 0.1\n",
      "699  Episode Reward:  227.50498591964237 .Epsilon: 0.1\n",
      "700  Episode Reward:  18.572304351852708 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "701  Episode Reward:  216.7778365525403 .Epsilon: 0.1\n",
      "702  Episode Reward:  238.38411933921174 .Epsilon: 0.1\n",
      "703  Episode Reward:  279.26496455478514 .Epsilon: 0.1\n",
      "704  Episode Reward:  -278.7343155256219 .Epsilon: 0.1\n",
      "705  Episode Reward:  -20.335173974911328 .Epsilon: 0.1\n",
      "706  Episode Reward:  10.972838227319173 .Epsilon: 0.1\n",
      "707  Episode Reward:  279.78761585783917 .Epsilon: 0.1\n",
      "708  Episode Reward:  283.0473109019345 .Epsilon: 0.1\n",
      "709  Episode Reward:  256.38381033100666 .Epsilon: 0.1\n",
      "710  Episode Reward:  197.74828677639505 .Epsilon: 0.1\n",
      "711  Episode Reward:  267.91930898136366 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "712  Episode Reward:  175.49189693190377 .Epsilon: 0.1\n",
      "713  Episode Reward:  301.54328580398817 .Epsilon: 0.1\n",
      "714  Episode Reward:  188.86035453160943 .Epsilon: 0.1\n",
      "715  Episode Reward:  256.340069181413 .Epsilon: 0.1\n",
      "716  Episode Reward:  -11.029890822526852 .Epsilon: 0.1\n",
      "717  Episode Reward:  43.83351361246736 .Epsilon: 0.1\n",
      "718  Episode Reward:  251.20036600504005 .Epsilon: 0.1\n",
      "719  Episode Reward:  239.42973151786256 .Epsilon: 0.1\n",
      "720  Episode Reward:  -221.08535187709987 .Epsilon: 0.1\n",
      "721  Episode Reward:  292.0074775168319 .Epsilon: 0.1\n",
      "722  Episode Reward:  -17.183220237479063 .Epsilon: 0.1\n",
      "723  Episode Reward:  -13.107414523993953 .Epsilon: 0.1\n",
      "724  Episode Reward:  31.291350858329167 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "725  Episode Reward:  265.9533149298632 .Epsilon: 0.1\n",
      "726  Episode Reward:  -33.07814396532625 .Epsilon: 0.1\n",
      "727  Episode Reward:  -190.2455935916995 .Epsilon: 0.1\n",
      "728  Episode Reward:  -84.258593620497 .Epsilon: 0.1\n",
      "729  Episode Reward:  -18.12187291287887 .Epsilon: 0.1\n",
      "730  Episode Reward:  247.5578994475402 .Epsilon: 0.1\n",
      "731  Episode Reward:  -141.32988925153097 .Epsilon: 0.1\n",
      "732  Episode Reward:  274.0392855597597 .Epsilon: 0.1\n",
      "733  Episode Reward:  -238.12327394606 .Epsilon: 0.1\n",
      "734  Episode Reward:  261.19859660986447 .Epsilon: 0.1\n",
      "735  Episode Reward:  -251.02820874231594 .Epsilon: 0.1\n",
      "736  Episode Reward:  242.45896275135635 .Epsilon: 0.1\n",
      "737  Episode Reward:  -197.18643473090816 .Epsilon: 0.1\n",
      "738  Episode Reward:  -200.1297020577096 .Epsilon: 0.1\n",
      "739  Episode Reward:  -40.175538346348105 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "740  Episode Reward:  -300.5451103573266 .Epsilon: 0.1\n",
      "741  Episode Reward:  245.54413092390388 .Epsilon: 0.1\n",
      "742  Episode Reward:  -450.8038197206996 .Epsilon: 0.1\n",
      "743  Episode Reward:  0.07573035783264004 .Epsilon: 0.1\n",
      "744  Episode Reward:  20.965869501864773 .Epsilon: 0.1\n",
      "745  Episode Reward:  -49.96928497767473 .Epsilon: 0.1\n",
      "746  Episode Reward:  -43.789288142409404 .Epsilon: 0.1\n",
      "747  Episode Reward:  -5.210388242591051 .Epsilon: 0.1\n",
      "748  Episode Reward:  -85.76136095063785 .Epsilon: 0.1\n",
      "749  Episode Reward:  241.12617532545153 .Epsilon: 0.1\n",
      "750  Episode Reward:  50.73624685307516 .Epsilon: 0.1\n",
      "751  Episode Reward:  -23.092597721947925 .Epsilon: 0.1\n",
      "752  Episode Reward:  231.9145961415917 .Epsilon: 0.1\n",
      "753  Episode Reward:  -15.206682052563224 .Epsilon: 0.1\n",
      "754  Episode Reward:  -266.52519695546806 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "755  Episode Reward:  260.4155788627851 .Epsilon: 0.1\n",
      "756  Episode Reward:  -171.96276167708075 .Epsilon: 0.1\n",
      "757  Episode Reward:  -140.90130674871165 .Epsilon: 0.1\n",
      "758  Episode Reward:  270.4958660823945 .Epsilon: 0.1\n",
      "759  Episode Reward:  254.2875658894059 .Epsilon: 0.1\n",
      "760  Episode Reward:  -119.33093858102642 .Epsilon: 0.1\n",
      "761  Episode Reward:  -5.188772811949121 .Epsilon: 0.1\n",
      "762  Episode Reward:  -52.725008321736716 .Epsilon: 0.1\n",
      "763  Episode Reward:  -180.92087254545282 .Epsilon: 0.1\n",
      "764  Episode Reward:  -31.94071911424132 .Epsilon: 0.1\n",
      "765  Episode Reward:  270.73649952560197 .Epsilon: 0.1\n",
      "766  Episode Reward:  269.4006630099557 .Epsilon: 0.1\n",
      "767  Episode Reward:  11.422641356572427 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "768  Episode Reward:  132.4739807852463 .Epsilon: 0.1\n",
      "769  Episode Reward:  -20.375955831352968 .Epsilon: 0.1\n",
      "770  Episode Reward:  38.807040132034246 .Epsilon: 0.1\n",
      "771  Episode Reward:  -135.79300625170552 .Epsilon: 0.1\n",
      "772  Episode Reward:  260.0352044284946 .Epsilon: 0.1\n",
      "773  Episode Reward:  -250.34106842393226 .Epsilon: 0.1\n",
      "774  Episode Reward:  273.6352076481103 .Epsilon: 0.1\n",
      "775  Episode Reward:  -12.168006106918526 .Epsilon: 0.1\n",
      "776  Episode Reward:  -83.69881709250498 .Epsilon: 0.1\n",
      "777  Episode Reward:  278.8776653874814 .Epsilon: 0.1\n",
      "778  Episode Reward:  -67.60006338908438 .Epsilon: 0.1\n",
      "779  Episode Reward:  36.63733669782118 .Epsilon: 0.1\n",
      "780  Episode Reward:  17.234629800528154 .Epsilon: 0.1\n",
      "781  Episode Reward:  18.65823524834248 .Epsilon: 0.1\n",
      "782  Episode Reward:  -212.66060043324978 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "783  Episode Reward:  288.74958991323507 .Epsilon: 0.1\n",
      "784  Episode Reward:  -8.864757379549175 .Epsilon: 0.1\n",
      "785  Episode Reward:  -331.78545959594123 .Epsilon: 0.1\n",
      "786  Episode Reward:  245.20317735434799 .Epsilon: 0.1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "787  Episode Reward:  12.719086154837242 .Epsilon: 0.1\n",
      "788  Episode Reward:  253.80128484308727 .Epsilon: 0.1\n",
      "789  Episode Reward:  -296.3932309008379 .Epsilon: 0.1\n",
      "790  Episode Reward:  228.23174256594078 .Epsilon: 0.1\n",
      "791  Episode Reward:  -130.20680242275836 .Epsilon: 0.1\n",
      "792  Episode Reward:  219.1216879429834 .Epsilon: 0.1\n",
      "793  Episode Reward:  -215.21923733100598 .Epsilon: 0.1\n",
      "794  Episode Reward:  27.383850467545685 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "795  Episode Reward:  -205.74836730827525 .Epsilon: 0.1\n",
      "796  Episode Reward:  12.731831859617571 .Epsilon: 0.1\n",
      "797  Episode Reward:  -153.01318382486429 .Epsilon: 0.1\n",
      "798  Episode Reward:  242.04791052395558 .Epsilon: 0.1\n",
      "799  Episode Reward:  -31.64403942249031 .Epsilon: 0.1\n",
      "800  Episode Reward:  27.21847916298293 .Epsilon: 0.1\n",
      "801  Episode Reward:  -53.1434824075137 .Epsilon: 0.1\n",
      "802  Episode Reward:  -244.25390921173675 .Epsilon: 0.1\n",
      "803  Episode Reward:  266.90587049300996 .Epsilon: 0.1\n",
      "804  Episode Reward:  35.70484927025237 .Epsilon: 0.1\n",
      "805  Episode Reward:  266.21310802059634 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "806  Episode Reward:  -284.6325565330121 .Epsilon: 0.1\n",
      "807  Episode Reward:  -220.18804391838404 .Epsilon: 0.1\n",
      "808  Episode Reward:  259.39922082234955 .Epsilon: 0.1\n",
      "809  Episode Reward:  -114.13023743770745 .Epsilon: 0.1\n",
      "810  Episode Reward:  -391.96120168101885 .Epsilon: 0.1\n",
      "811  Episode Reward:  271.98811588287583 .Epsilon: 0.1\n",
      "812  Episode Reward:  253.6726885409371 .Epsilon: 0.1\n",
      "813  Episode Reward:  278.92557806073785 .Epsilon: 0.1\n",
      "814  Episode Reward:  267.2156054366277 .Epsilon: 0.1\n",
      "815  Episode Reward:  272.47100222282097 .Epsilon: 0.1\n",
      "816  Episode Reward:  43.650043269318786 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "817  Episode Reward:  14.867091969985779 .Epsilon: 0.1\n",
      "818  Episode Reward:  254.52347797136213 .Epsilon: 0.1\n",
      "819  Episode Reward:  236.97942328516106 .Epsilon: 0.1\n",
      "820  Episode Reward:  217.77539810395223 .Epsilon: 0.1\n",
      "821  Episode Reward:  -246.1650252851692 .Epsilon: 0.1\n",
      "822  Episode Reward:  -113.28016112849103 .Epsilon: 0.1\n",
      "823  Episode Reward:  -383.23480466429936 .Epsilon: 0.1\n",
      "824  Episode Reward:  -290.13038702168546 .Epsilon: 0.1\n",
      "825  Episode Reward:  9.753551913874531 .Epsilon: 0.1\n",
      "826  Episode Reward:  224.0258691586003 .Epsilon: 0.1\n",
      "827  Episode Reward:  -48.85849487955588 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "828  Episode Reward:  -30.695950604721773 .Epsilon: 0.1\n",
      "829  Episode Reward:  -53.11269463698423 .Epsilon: 0.1\n",
      "830  Episode Reward:  -12.383945309346984 .Epsilon: 0.1\n",
      "831  Episode Reward:  -207.17528149682272 .Epsilon: 0.1\n",
      "832  Episode Reward:  -54.27090843272488 .Epsilon: 0.1\n",
      "833  Episode Reward:  276.34841552946375 .Epsilon: 0.1\n",
      "834  Episode Reward:  -1.8694606444289263 .Epsilon: 0.1\n",
      "835  Episode Reward:  -89.28306296134859 .Epsilon: 0.1\n",
      "836  Episode Reward:  236.28258643710166 .Epsilon: 0.1\n",
      "837  Episode Reward:  236.03423622875425 .Epsilon: 0.1\n",
      "838  Episode Reward:  245.66499248004658 .Epsilon: 0.1\n",
      "839  Episode Reward:  268.66548592578795 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "840  Episode Reward:  258.6037664139884 .Epsilon: 0.1\n",
      "841  Episode Reward:  302.50836156381797 .Epsilon: 0.1\n",
      "842  Episode Reward:  224.14268305146442 .Epsilon: 0.1\n",
      "843  Episode Reward:  -154.6177805093626 .Epsilon: 0.1\n",
      "844  Episode Reward:  266.6388648734974 .Epsilon: 0.1\n",
      "845  Episode Reward:  -189.96036047001655 .Epsilon: 0.1\n",
      "846  Episode Reward:  292.1515010753494 .Epsilon: 0.1\n",
      "847  Episode Reward:  -54.096591690294076 .Epsilon: 0.1\n",
      "848  Episode Reward:  -63.325315391466226 .Epsilon: 0.1\n",
      "849  Episode Reward:  268.8858481837848 .Epsilon: 0.1\n",
      "850  Episode Reward:  -261.9410705894092 .Epsilon: 0.1\n",
      "851  Episode Reward:  40.82567006085108 .Epsilon: 0.1\n",
      "852  Episode Reward:  21.021378576639805 .Epsilon: 0.1\n",
      "853  Episode Reward:  -14.282077699498984 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "854  Episode Reward:  298.78574816998724 .Epsilon: 0.1\n",
      "855  Episode Reward:  287.1593459352369 .Epsilon: 0.1\n",
      "856  Episode Reward:  -4.588398917698498 .Epsilon: 0.1\n",
      "857  Episode Reward:  -159.38509770091827 .Epsilon: 0.1\n",
      "858  Episode Reward:  -16.805877703543544 .Epsilon: 0.1\n",
      "859  Episode Reward:  265.3999996533381 .Epsilon: 0.1\n",
      "860  Episode Reward:  -14.745231363771694 .Epsilon: 0.1\n",
      "861  Episode Reward:  1.167175479830135 .Epsilon: 0.1\n",
      "862  Episode Reward:  -39.570420996093794 .Epsilon: 0.1\n",
      "863  Episode Reward:  225.86573094672735 .Epsilon: 0.1\n",
      "864  Episode Reward:  -49.30991732222569 .Epsilon: 0.1\n",
      "865  Episode Reward:  -222.83362754197347 .Epsilon: 0.1\n",
      "866  Episode Reward:  238.1504440397761 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "867  Episode Reward:  246.1793129745154 .Epsilon: 0.1\n",
      "868  Episode Reward:  -198.5322752665046 .Epsilon: 0.1\n",
      "869  Episode Reward:  262.2643064921026 .Epsilon: 0.1\n",
      "870  Episode Reward:  -291.1679660404043 .Epsilon: 0.1\n",
      "871  Episode Reward:  277.7683865214677 .Epsilon: 0.1\n",
      "872  Episode Reward:  -24.396328665065823 .Epsilon: 0.1\n",
      "873  Episode Reward:  -206.4270178533345 .Epsilon: 0.1\n",
      "874  Episode Reward:  -379.2251295376888 .Epsilon: 0.1\n",
      "875  Episode Reward:  24.31518049299582 .Epsilon: 0.1\n",
      "876  Episode Reward:  -63.45338436692756 .Epsilon: 0.1\n",
      "877  Episode Reward:  -60.40097195957874 .Epsilon: 0.1\n",
      "878  Episode Reward:  3.1772020799097476 .Epsilon: 0.1\n",
      "879  Episode Reward:  -90.98343075956787 .Epsilon: 0.1\n",
      "880  Episode Reward:  257.69572438681695 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "881  Episode Reward:  270.5180325229654 .Epsilon: 0.1\n",
      "882  Episode Reward:  -139.7985272583911 .Epsilon: 0.1\n",
      "883  Episode Reward:  253.18036192031605 .Epsilon: 0.1\n",
      "884  Episode Reward:  7.70783725293154 .Epsilon: 0.1\n",
      "885  Episode Reward:  -238.8629003441761 .Epsilon: 0.1\n",
      "886  Episode Reward:  266.67709686868454 .Epsilon: 0.1\n",
      "887  Episode Reward:  237.98876127883838 .Epsilon: 0.1\n",
      "888  Episode Reward:  234.50032363354282 .Epsilon: 0.1\n",
      "889  Episode Reward:  286.6331602702393 .Epsilon: 0.1\n",
      "890  Episode Reward:  271.9068326538802 .Epsilon: 0.1\n",
      "891  Episode Reward:  275.2112867321841 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "892  Episode Reward:  2.935109015596808 .Epsilon: 0.1\n",
      "893  Episode Reward:  -25.833277947746197 .Epsilon: 0.1\n",
      "894  Episode Reward:  243.01872486296114 .Epsilon: 0.1\n",
      "895  Episode Reward:  257.2600573415192 .Epsilon: 0.1\n",
      "896  Episode Reward:  252.41310720282445 .Epsilon: 0.1\n",
      "897  Episode Reward:  282.5660367185902 .Epsilon: 0.1\n",
      "898  Episode Reward:  18.948042449754197 .Epsilon: 0.1\n",
      "899  Episode Reward:  295.51765873312297 .Epsilon: 0.1\n",
      "900  Episode Reward:  -147.6451541761283 .Epsilon: 0.1\n",
      "901  Episode Reward:  -27.671552748622815 .Epsilon: 0.1\n",
      "902  Episode Reward:  277.55096885940463 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "903  Episode Reward:  274.8237849878974 .Epsilon: 0.1\n",
      "904  Episode Reward:  -504.3489741048732 .Epsilon: 0.1\n",
      "905  Episode Reward:  250.31277651089977 .Epsilon: 0.1\n",
      "906  Episode Reward:  54.54119191861611 .Epsilon: 0.1\n",
      "907  Episode Reward:  259.13957225085863 .Epsilon: 0.1\n",
      "908  Episode Reward:  0.9162062352736342 .Epsilon: 0.1\n",
      "909  Episode Reward:  -171.48421753677644 .Epsilon: 0.1\n",
      "910  Episode Reward:  245.6158647976178 .Epsilon: 0.1\n",
      "911  Episode Reward:  -250.8714698830553 .Epsilon: 0.1\n",
      "912  Episode Reward:  240.33399352893557 .Epsilon: 0.1\n",
      "913  Episode Reward:  -395.1835819221274 .Epsilon: 0.1\n",
      "914  Episode Reward:  -314.57029704458284 .Epsilon: 0.1\n",
      "915  Episode Reward:  50.22861414874566 .Epsilon: 0.1\n",
      "916  Episode Reward:  -63.49298857132395 .Epsilon: 0.1\n",
      "917  Episode Reward:  20.693589927104895 .Epsilon: 0.1\n",
      "918  Episode Reward:  -135.19929907435306 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "919  Episode Reward:  1.8468008399620714 .Epsilon: 0.1\n",
      "920  Episode Reward:  -56.11548626619041 .Epsilon: 0.1\n",
      "921  Episode Reward:  49.746114315052324 .Epsilon: 0.1\n",
      "922  Episode Reward:  -84.59548275478033 .Epsilon: 0.1\n",
      "923  Episode Reward:  293.1238006650935 .Epsilon: 0.1\n",
      "924  Episode Reward:  -304.7443434210177 .Epsilon: 0.1\n",
      "925  Episode Reward:  177.06545083377404 .Epsilon: 0.1\n",
      "926  Episode Reward:  -139.02721789992742 .Epsilon: 0.1\n",
      "927  Episode Reward:  271.8961942550851 .Epsilon: 0.1\n",
      "928  Episode Reward:  -77.09991325516505 .Epsilon: 0.1\n",
      "929  Episode Reward:  -229.35787569703658 .Epsilon: 0.1\n",
      "930  Episode Reward:  -331.6807975248098 .Epsilon: 0.1\n",
      "931  Episode Reward:  -76.39829746212777 .Epsilon: 0.1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "932  Episode Reward:  -78.0522589810595 .Epsilon: 0.1\n",
      "933  Episode Reward:  -62.40382418922319 .Epsilon: 0.1\n",
      "934  Episode Reward:  -360.3539071635833 .Epsilon: 0.1\n",
      "935  Episode Reward:  -82.6662608763703 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "936  Episode Reward:  257.90378535894854 .Epsilon: 0.1\n",
      "937  Episode Reward:  -190.43923344021175 .Epsilon: 0.1\n",
      "938  Episode Reward:  -348.1569466927139 .Epsilon: 0.1\n",
      "939  Episode Reward:  -69.20397321974072 .Epsilon: 0.1\n",
      "940  Episode Reward:  251.1795572207647 .Epsilon: 0.1\n",
      "941  Episode Reward:  -256.7747341712492 .Epsilon: 0.1\n",
      "942  Episode Reward:  -307.5861703963366 .Epsilon: 0.1\n",
      "943  Episode Reward:  -263.8472651598323 .Epsilon: 0.1\n",
      "944  Episode Reward:  274.5058725446514 .Epsilon: 0.1\n",
      "945  Episode Reward:  -222.4315884742147 .Epsilon: 0.1\n",
      "946  Episode Reward:  -305.98255843014283 .Epsilon: 0.1\n",
      "947  Episode Reward:  -95.09249117794384 .Epsilon: 0.1\n",
      "948  Episode Reward:  40.7106213834021 .Epsilon: 0.1\n",
      "949  Episode Reward:  -17.95540989566834 .Epsilon: 0.1\n",
      "950  Episode Reward:  -141.2507816603699 .Epsilon: 0.1\n",
      "951  Episode Reward:  -175.55823952661584 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "952  Episode Reward:  141.0175979195096 .Epsilon: 0.1\n",
      "953  Episode Reward:  212.40348006115633 .Epsilon: 0.1\n",
      "954  Episode Reward:  -334.95664367041263 .Epsilon: 0.1\n",
      "955  Episode Reward:  -49.80490137723848 .Epsilon: 0.1\n",
      "956  Episode Reward:  -224.81139140238733 .Epsilon: 0.1\n",
      "957  Episode Reward:  -175.76215146537518 .Epsilon: 0.1\n",
      "958  Episode Reward:  261.075676795343 .Epsilon: 0.1\n",
      "959  Episode Reward:  -268.6740662632924 .Epsilon: 0.1\n",
      "960  Episode Reward:  -220.0399611133402 .Epsilon: 0.1\n",
      "961  Episode Reward:  297.20233497028835 .Epsilon: 0.1\n",
      "962  Episode Reward:  -217.34603228979276 .Epsilon: 0.1\n",
      "963  Episode Reward:  -17.331523130502788 .Epsilon: 0.1\n",
      "964  Episode Reward:  34.84074334481855 .Epsilon: 0.1\n",
      "965  Episode Reward:  216.22896148813635 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "966  Episode Reward:  271.3780858690354 .Epsilon: 0.1\n",
      "967  Episode Reward:  -44.233900360178566 .Epsilon: 0.1\n",
      "968  Episode Reward:  -46.372637894001016 .Epsilon: 0.1\n",
      "969  Episode Reward:  -21.53920150690176 .Epsilon: 0.1\n",
      "970  Episode Reward:  -239.61919047595032 .Epsilon: 0.1\n",
      "971  Episode Reward:  5.9325458772060955 .Epsilon: 0.1\n",
      "972  Episode Reward:  236.45742339929518 .Epsilon: 0.1\n",
      "973  Episode Reward:  -10.353105003390539 .Epsilon: 0.1\n",
      "974  Episode Reward:  -46.567740492372025 .Epsilon: 0.1\n",
      "975  Episode Reward:  260.09405721600547 .Epsilon: 0.1\n",
      "976  Episode Reward:  -236.70059544517335 .Epsilon: 0.1\n",
      "977  Episode Reward:  284.64414575098823 .Epsilon: 0.1\n",
      "978  Episode Reward:  248.92143197850288 .Epsilon: 0.1\n",
      "979  Episode Reward:  -260.5817288348836 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "980  Episode Reward:  273.93009919616566 .Epsilon: 0.1\n",
      "981  Episode Reward:  -60.66004223890066 .Epsilon: 0.1\n",
      "982  Episode Reward:  47.51160060832947 .Epsilon: 0.1\n",
      "983  Episode Reward:  241.90198674268981 .Epsilon: 0.1\n",
      "984  Episode Reward:  -89.77069677297581 .Epsilon: 0.1\n",
      "985  Episode Reward:  -193.13977337410216 .Epsilon: 0.1\n",
      "986  Episode Reward:  -275.401220388511 .Epsilon: 0.1\n",
      "987  Episode Reward:  -48.80971610158287 .Epsilon: 0.1\n",
      "988  Episode Reward:  264.55555870025705 .Epsilon: 0.1\n",
      "989  Episode Reward:  -262.8829548460527 .Epsilon: 0.1\n",
      "990  Episode Reward:  -234.35879678405797 .Epsilon: 0.1\n",
      "991  Episode Reward:  -117.72433217199901 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "992  Episode Reward:  -313.4158348818921 .Epsilon: 0.1\n",
      "993  Episode Reward:  -130.26290602059072 .Epsilon: 0.1\n",
      "994  Episode Reward:  -135.59086527381675 .Epsilon: 0.1\n",
      "995  Episode Reward:  -300.9982221353072 .Epsilon: 0.1\n",
      "996  Episode Reward:  -36.28458169594994 .Epsilon: 0.1\n",
      "997  Episode Reward:  -233.97268627418822 .Epsilon: 0.1\n",
      "998  Episode Reward:  271.9579052067059 .Epsilon: 0.1\n",
      "999  Episode Reward:  228.7959574122533 .Epsilon: 0.1\n",
      "1000  Episode Reward:  -158.09757615338555 .Epsilon: 0.1\n",
      "1001  Episode Reward:  17.165829020583644 .Epsilon: 0.1\n",
      "1002  Episode Reward:  297.4158202776945 .Epsilon: 0.1\n",
      "1003  Episode Reward:  -513.137827556868 .Epsilon: 0.1\n",
      "1004  Episode Reward:  -164.3868905741628 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1005  Episode Reward:  24.127360031184708 .Epsilon: 0.1\n",
      "1006  Episode Reward:  -139.88977488947955 .Epsilon: 0.1\n",
      "1007  Episode Reward:  -114.82631153353498 .Epsilon: 0.1\n",
      "1008  Episode Reward:  -283.83393762948856 .Epsilon: 0.1\n",
      "1009  Episode Reward:  -223.51798212164226 .Epsilon: 0.1\n",
      "1010  Episode Reward:  -269.7865206514332 .Epsilon: 0.1\n",
      "1011  Episode Reward:  -164.6119267852636 .Epsilon: 0.1\n",
      "1012  Episode Reward:  -171.38034504385263 .Epsilon: 0.1\n",
      "1013  Episode Reward:  221.3398406611031 .Epsilon: 0.1\n",
      "1014  Episode Reward:  251.01470788523966 .Epsilon: 0.1\n",
      "1015  Episode Reward:  290.17815406437245 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1016  Episode Reward:  237.76287659976964 .Epsilon: 0.1\n",
      "1017  Episode Reward:  279.5717568479301 .Epsilon: 0.1\n",
      "1018  Episode Reward:  8.100432977587147 .Epsilon: 0.1\n",
      "1019  Episode Reward:  -10.002263950349018 .Epsilon: 0.1\n",
      "1020  Episode Reward:  -270.48117266921577 .Epsilon: 0.1\n",
      "1021  Episode Reward:  -21.054870295418752 .Epsilon: 0.1\n",
      "1022  Episode Reward:  66.61040723605785 .Epsilon: 0.1\n",
      "1023  Episode Reward:  277.98614584837327 .Epsilon: 0.1\n",
      "1024  Episode Reward:  298.0360141219973 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1025  Episode Reward:  264.7651241755724 .Epsilon: 0.1\n",
      "1026  Episode Reward:  277.5807440033892 .Epsilon: 0.1\n",
      "1027  Episode Reward:  -317.7648386534526 .Epsilon: 0.1\n",
      "1028  Episode Reward:  -181.06988407526052 .Epsilon: 0.1\n",
      "1029  Episode Reward:  216.9807203238388 .Epsilon: 0.1\n",
      "1030  Episode Reward:  47.854284525680924 .Epsilon: 0.1\n",
      "1031  Episode Reward:  290.54184345171814 .Epsilon: 0.1\n",
      "1032  Episode Reward:  -23.589988844508056 .Epsilon: 0.1\n",
      "1033  Episode Reward:  280.7567833572616 .Epsilon: 0.1\n",
      "1034  Episode Reward:  -63.09490736598394 .Epsilon: 0.1\n",
      "1035  Episode Reward:  -280.7814166415906 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1036  Episode Reward:  -144.39401913472884 .Epsilon: 0.1\n",
      "1037  Episode Reward:  235.92926540213793 .Epsilon: 0.1\n",
      "1038  Episode Reward:  -277.178529280529 .Epsilon: 0.1\n",
      "1039  Episode Reward:  290.41512704028594 .Epsilon: 0.1\n",
      "1040  Episode Reward:  261.9646742649928 .Epsilon: 0.1\n",
      "1041  Episode Reward:  30.546746126582946 .Epsilon: 0.1\n",
      "1042  Episode Reward:  280.9213885452547 .Epsilon: 0.1\n",
      "1043  Episode Reward:  278.62353139099355 .Epsilon: 0.1\n",
      "1044  Episode Reward:  307.20081338170155 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1045  Episode Reward:  299.5864657562034 .Epsilon: 0.1\n",
      "1046  Episode Reward:  250.11531994328067 .Epsilon: 0.1\n",
      "1047  Episode Reward:  -82.5677299240978 .Epsilon: 0.1\n",
      "1048  Episode Reward:  292.4999273197516 .Epsilon: 0.1\n",
      "1049  Episode Reward:  -12.269555752121278 .Epsilon: 0.1\n",
      "1050  Episode Reward:  -119.46046781968433 .Epsilon: 0.1\n",
      "1051  Episode Reward:  -8.066267017827997 .Epsilon: 0.1\n",
      "1052  Episode Reward:  287.5386446758315 .Epsilon: 0.1\n",
      "1053  Episode Reward:  -161.53532381315995 .Epsilon: 0.1\n",
      "1054  Episode Reward:  -220.86489862907789 .Epsilon: 0.1\n",
      "1055  Episode Reward:  272.2223175830335 .Epsilon: 0.1\n",
      "1056  Episode Reward:  270.6579214623059 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1057  Episode Reward:  250.6429582775404 .Epsilon: 0.1\n",
      "1058  Episode Reward:  31.32001246133231 .Epsilon: 0.1\n",
      "1059  Episode Reward:  264.59564222067763 .Epsilon: 0.1\n",
      "1060  Episode Reward:  261.57162762633834 .Epsilon: 0.1\n",
      "1061  Episode Reward:  249.93107028320128 .Epsilon: 0.1\n",
      "1062  Episode Reward:  308.8814096969927 .Epsilon: 0.1\n",
      "1063  Episode Reward:  297.6983896660796 .Epsilon: 0.1\n",
      "1064  Episode Reward:  248.3833945991733 .Epsilon: 0.1\n",
      "1065  Episode Reward:  -176.46245657224262 .Epsilon: 0.1\n",
      "1066  Episode Reward:  236.0428428979581 .Epsilon: 0.1\n",
      "1067  Episode Reward:  270.7610478112074 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1068  Episode Reward:  287.9373574566239 .Epsilon: 0.1\n",
      "1069  Episode Reward:  -91.35707062370216 .Epsilon: 0.1\n",
      "1070  Episode Reward:  -35.93784596260903 .Epsilon: 0.1\n",
      "1071  Episode Reward:  -83.4679783158502 .Epsilon: 0.1\n",
      "1072  Episode Reward:  26.400595484562714 .Epsilon: 0.1\n",
      "1073  Episode Reward:  251.60083181939603 .Epsilon: 0.1\n",
      "1074  Episode Reward:  21.694734792414195 .Epsilon: 0.1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1075  Episode Reward:  -62.33757905064579 .Epsilon: 0.1\n",
      "1076  Episode Reward:  253.1767095752744 .Epsilon: 0.1\n",
      "1077  Episode Reward:  58.09910326706955 .Epsilon: 0.1\n",
      "1078  Episode Reward:  227.2367862705065 .Epsilon: 0.1\n",
      "1079  Episode Reward:  -45.14607102341243 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1080  Episode Reward:  -256.81967095624157 .Epsilon: 0.1\n",
      "1081  Episode Reward:  -90.82293776761902 .Epsilon: 0.1\n",
      "1082  Episode Reward:  -243.03396694612894 .Epsilon: 0.1\n",
      "1083  Episode Reward:  -240.6799440263334 .Epsilon: 0.1\n",
      "1084  Episode Reward:  172.6137769800315 .Epsilon: 0.1\n",
      "1085  Episode Reward:  267.90298300687493 .Epsilon: 0.1\n",
      "1086  Episode Reward:  293.9966568289727 .Epsilon: 0.1\n",
      "1087  Episode Reward:  227.80059103720686 .Epsilon: 0.1\n",
      "1088  Episode Reward:  -10.712393649653933 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1089  Episode Reward:  295.1382530169625 .Epsilon: 0.1\n",
      "1090  Episode Reward:  18.231463169078353 .Epsilon: 0.1\n",
      "1091  Episode Reward:  -293.24349412548577 .Epsilon: 0.1\n",
      "1092  Episode Reward:  -144.32858395744296 .Epsilon: 0.1\n",
      "1093  Episode Reward:  278.05658320036923 .Epsilon: 0.1\n",
      "1094  Episode Reward:  -269.8418064171807 .Epsilon: 0.1\n",
      "1095  Episode Reward:  -72.9356747021231 .Epsilon: 0.1\n",
      "1096  Episode Reward:  -213.7895382476941 .Epsilon: 0.1\n",
      "1097  Episode Reward:  237.48875961560242 .Epsilon: 0.1\n",
      "1098  Episode Reward:  -212.04118355512566 .Epsilon: 0.1\n",
      "1099  Episode Reward:  -189.88981690972355 .Epsilon: 0.1\n",
      "1100  Episode Reward:  265.36788759787714 .Epsilon: 0.1\n",
      "1101  Episode Reward:  -122.36066298333736 .Epsilon: 0.1\n",
      "1102  Episode Reward:  -78.30107525443405 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1103  Episode Reward:  260.4146494590261 .Epsilon: 0.1\n",
      "1104  Episode Reward:  -103.61582917598848 .Epsilon: 0.1\n",
      "1105  Episode Reward:  11.062760030620964 .Epsilon: 0.1\n",
      "1106  Episode Reward:  -15.792530092743931 .Epsilon: 0.1\n",
      "1107  Episode Reward:  262.96008585004313 .Epsilon: 0.1\n",
      "1108  Episode Reward:  14.250832095896968 .Epsilon: 0.1\n",
      "1109  Episode Reward:  274.8531686397136 .Epsilon: 0.1\n",
      "1110  Episode Reward:  269.5184567106839 .Epsilon: 0.1\n",
      "1111  Episode Reward:  270.2228026250723 .Epsilon: 0.1\n",
      "1112  Episode Reward:  238.71682158068018 .Epsilon: 0.1\n",
      "1113  Episode Reward:  -38.25041397396964 .Epsilon: 0.1\n",
      "1114  Episode Reward:  -16.869119207790902 .Epsilon: 0.1\n",
      "1115  Episode Reward:  271.74593167987325 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1116  Episode Reward:  24.90040717784555 .Epsilon: 0.1\n",
      "1117  Episode Reward:  -4.423597861906231 .Epsilon: 0.1\n",
      "1118  Episode Reward:  3.9967164263941015 .Epsilon: 0.1\n",
      "1119  Episode Reward:  -69.23174324510309 .Epsilon: 0.1\n",
      "1120  Episode Reward:  -206.16618245255825 .Epsilon: 0.1\n",
      "1121  Episode Reward:  155.88878366463894 .Epsilon: 0.1\n",
      "1122  Episode Reward:  285.72529944686636 .Epsilon: 0.1\n",
      "1123  Episode Reward:  261.23145753992094 .Epsilon: 0.1\n",
      "1124  Episode Reward:  269.42319456156497 .Epsilon: 0.1\n",
      "1125  Episode Reward:  -256.8657264473947 .Epsilon: 0.1\n",
      "1126  Episode Reward:  20.45475529871183 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1127  Episode Reward:  244.24954253308846 .Epsilon: 0.1\n",
      "1128  Episode Reward:  280.7771367545446 .Epsilon: 0.1\n",
      "1129  Episode Reward:  -195.95410191021784 .Epsilon: 0.1\n",
      "1130  Episode Reward:  -321.5630896468606 .Epsilon: 0.1\n",
      "1131  Episode Reward:  19.683133089848994 .Epsilon: 0.1\n",
      "1132  Episode Reward:  -43.243442069596775 .Epsilon: 0.1\n",
      "1133  Episode Reward:  -151.64870264874725 .Epsilon: 0.1\n",
      "1134  Episode Reward:  3.467099009977332 .Epsilon: 0.1\n",
      "1135  Episode Reward:  -50.746296626452036 .Epsilon: 0.1\n",
      "1136  Episode Reward:  -55.289084443143366 .Epsilon: 0.1\n",
      "1137  Episode Reward:  291.02727706290966 .Epsilon: 0.1\n",
      "1138  Episode Reward:  235.62914307391122 .Epsilon: 0.1\n",
      "1139  Episode Reward:  -20.306663600917133 .Epsilon: 0.1\n",
      "1140  Episode Reward:  311.6093584107839 .Epsilon: 0.1\n",
      "1141  Episode Reward:  -83.4658892686473 .Epsilon: 0.1\n",
      "1142  Episode Reward:  270.40555659386223 .Epsilon: 0.1\n",
      "1143  Episode Reward:  -60.70107853603699 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1144  Episode Reward:  218.41504003156197 .Epsilon: 0.1\n",
      "1145  Episode Reward:  274.02565470360264 .Epsilon: 0.1\n",
      "1146  Episode Reward:  291.197032047627 .Epsilon: 0.1\n",
      "1147  Episode Reward:  295.5713103815838 .Epsilon: 0.1\n",
      "1148  Episode Reward:  2.2555314160273383 .Epsilon: 0.1\n",
      "1149  Episode Reward:  12.6986309838274 .Epsilon: 0.1\n",
      "1150  Episode Reward:  -105.39301673714665 .Epsilon: 0.1\n",
      "1151  Episode Reward:  -241.40083634954246 .Epsilon: 0.1\n",
      "1152  Episode Reward:  -234.6350266195462 .Epsilon: 0.1\n",
      "1153  Episode Reward:  167.23617390682324 .Epsilon: 0.1\n",
      "1154  Episode Reward:  5.042526957040195 .Epsilon: 0.1\n",
      "1155  Episode Reward:  267.3811530187144 .Epsilon: 0.1\n",
      "1156  Episode Reward:  296.476910104132 .Epsilon: 0.1\n",
      "1157  Episode Reward:  -67.2815114807643 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1158  Episode Reward:  272.9992806588953 .Epsilon: 0.1\n",
      "1159  Episode Reward:  261.5969691189933 .Epsilon: 0.1\n",
      "1160  Episode Reward:  211.49872440338197 .Epsilon: 0.1\n",
      "1161  Episode Reward:  290.69399797992423 .Epsilon: 0.1\n",
      "1162  Episode Reward:  231.3029350016946 .Epsilon: 0.1\n",
      "1163  Episode Reward:  275.4589740715118 .Epsilon: 0.1\n",
      "1164  Episode Reward:  260.20508578709655 .Epsilon: 0.1\n",
      "1165  Episode Reward:  263.3068137302905 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1166  Episode Reward:  -237.8674792169099 .Epsilon: 0.1\n",
      "1167  Episode Reward:  -34.36805527676334 .Epsilon: 0.1\n",
      "1168  Episode Reward:  288.4150337258919 .Epsilon: 0.1\n",
      "1169  Episode Reward:  228.0659247931418 .Epsilon: 0.1\n",
      "1170  Episode Reward:  -230.3311174517371 .Epsilon: 0.1\n",
      "1171  Episode Reward:  264.38413143992807 .Epsilon: 0.1\n",
      "1172  Episode Reward:  261.4264212652837 .Epsilon: 0.1\n",
      "1173  Episode Reward:  -111.21617852443008 .Epsilon: 0.1\n",
      "1174  Episode Reward:  -212.1435436816384 .Epsilon: 0.1\n",
      "1175  Episode Reward:  268.48564620573586 .Epsilon: 0.1\n",
      "1176  Episode Reward:  -273.8753698236246 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1177  Episode Reward:  231.86967532417145 .Epsilon: 0.1\n",
      "1178  Episode Reward:  265.8293111788587 .Epsilon: 0.1\n",
      "1179  Episode Reward:  253.9988223463136 .Epsilon: 0.1\n",
      "1180  Episode Reward:  210.70828691817135 .Epsilon: 0.1\n",
      "1181  Episode Reward:  232.3180030946702 .Epsilon: 0.1\n",
      "1182  Episode Reward:  -132.9575536278849 .Epsilon: 0.1\n",
      "1183  Episode Reward:  -403.9198826059832 .Epsilon: 0.1\n",
      "1184  Episode Reward:  -257.7771970208315 .Epsilon: 0.1\n",
      "1185  Episode Reward:  19.153919109221178 .Epsilon: 0.1\n",
      "1186  Episode Reward:  -389.0933252892192 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1187  Episode Reward:  -249.24359086211462 .Epsilon: 0.1\n",
      "1188  Episode Reward:  7.435143457846095 .Epsilon: 0.1\n",
      "1189  Episode Reward:  -68.24546085111564 .Epsilon: 0.1\n",
      "1190  Episode Reward:  271.1793433018513 .Epsilon: 0.1\n",
      "1191  Episode Reward:  -139.27927732563188 .Epsilon: 0.1\n",
      "1192  Episode Reward:  143.2670935107192 .Epsilon: 0.1\n",
      "1193  Episode Reward:  242.97759801927697 .Epsilon: 0.1\n",
      "1194  Episode Reward:  -9.836011584419865 .Epsilon: 0.1\n",
      "1195  Episode Reward:  -199.59829607347996 .Epsilon: 0.1\n",
      "1196  Episode Reward:  273.42269723851115 .Epsilon: 0.1\n",
      "1197  Episode Reward:  210.37732981341688 .Epsilon: 0.1\n",
      "1198  Episode Reward:  275.788743344086 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1199  Episode Reward:  -241.65955064277625 .Epsilon: 0.1\n",
      "1200  Episode Reward:  246.1922863558257 .Epsilon: 0.1\n",
      "1201  Episode Reward:  12.955095981524636 .Epsilon: 0.1\n",
      "1202  Episode Reward:  1.9832970536437529 .Epsilon: 0.1\n",
      "1203  Episode Reward:  290.5742240667776 .Epsilon: 0.1\n",
      "1204  Episode Reward:  27.139173255582662 .Epsilon: 0.1\n",
      "1205  Episode Reward:  -242.61483029149394 .Epsilon: 0.1\n",
      "1206  Episode Reward:  -248.2581384553834 .Epsilon: 0.1\n",
      "1207  Episode Reward:  271.1256711798951 .Epsilon: 0.1\n",
      "1208  Episode Reward:  -133.82723751162985 .Epsilon: 0.1\n",
      "1209  Episode Reward:  289.27041527304976 .Epsilon: 0.1\n",
      "1210  Episode Reward:  255.75092028730154 .Epsilon: 0.1\n",
      "1211  Episode Reward:  -284.28730191420885 .Epsilon: 0.1\n",
      "1212  Episode Reward:  -275.3494429819967 .Epsilon: 0.1\n",
      "1213  Episode Reward:  -205.76556995851695 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1214  Episode Reward:  216.57135298728332 .Epsilon: 0.1\n",
      "1215  Episode Reward:  5.374453497330819 .Epsilon: 0.1\n",
      "1216  Episode Reward:  -178.7604647719505 .Epsilon: 0.1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1217  Episode Reward:  -250.00995201904223 .Epsilon: 0.1\n",
      "1218  Episode Reward:  7.310235573595477 .Epsilon: 0.1\n",
      "1219  Episode Reward:  -103.14041554616851 .Epsilon: 0.1\n",
      "1220  Episode Reward:  -122.42633348795657 .Epsilon: 0.1\n",
      "1221  Episode Reward:  -149.03682948264463 .Epsilon: 0.1\n",
      "1222  Episode Reward:  281.2101510116486 .Epsilon: 0.1\n",
      "1223  Episode Reward:  -93.07327607207732 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1224  Episode Reward:  -181.68665250062267 .Epsilon: 0.1\n",
      "1225  Episode Reward:  -35.41850704374299 .Epsilon: 0.1\n",
      "1226  Episode Reward:  264.43266049238946 .Epsilon: 0.1\n",
      "1227  Episode Reward:  -170.3441694914498 .Epsilon: 0.1\n",
      "1228  Episode Reward:  257.60024425545146 .Epsilon: 0.1\n",
      "1229  Episode Reward:  254.76633742521287 .Epsilon: 0.1\n",
      "1230  Episode Reward:  261.98121177879796 .Epsilon: 0.1\n",
      "1231  Episode Reward:  -147.7827997673837 .Epsilon: 0.1\n",
      "1232  Episode Reward:  269.05900011415224 .Epsilon: 0.1\n",
      "1233  Episode Reward:  -25.843462920323645 .Epsilon: 0.1\n",
      "1234  Episode Reward:  33.38611869495 .Epsilon: 0.1\n",
      "1235  Episode Reward:  -196.01019607947848 .Epsilon: 0.1\n",
      "1236  Episode Reward:  -11.080402978830008 .Epsilon: 0.1\n",
      "1237  Episode Reward:  31.456981388761363 .Epsilon: 0.1\n",
      "1238  Episode Reward:  -59.08838286845929 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1239  Episode Reward:  -55.16257859977357 .Epsilon: 0.1\n",
      "1240  Episode Reward:  -114.16929408684877 .Epsilon: 0.1\n",
      "1241  Episode Reward:  -166.9402124200941 .Epsilon: 0.1\n",
      "1242  Episode Reward:  278.591866208749 .Epsilon: 0.1\n",
      "1243  Episode Reward:  202.1495247303447 .Epsilon: 0.1\n",
      "1244  Episode Reward:  184.15504465916143 .Epsilon: 0.1\n",
      "1245  Episode Reward:  23.325595231130563 .Epsilon: 0.1\n",
      "1246  Episode Reward:  249.4178623698477 .Epsilon: 0.1\n",
      "1247  Episode Reward:  258.1520256464921 .Epsilon: 0.1\n",
      "1248  Episode Reward:  -2.216717259758653 .Epsilon: 0.1\n",
      "1249  Episode Reward:  291.33274614114174 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1250  Episode Reward:  269.6844985231469 .Epsilon: 0.1\n",
      "1251  Episode Reward:  -119.49879808500002 .Epsilon: 0.1\n",
      "1252  Episode Reward:  251.29633497589327 .Epsilon: 0.1\n",
      "1253  Episode Reward:  280.79646775971526 .Epsilon: 0.1\n",
      "1254  Episode Reward:  11.671332762060231 .Epsilon: 0.1\n",
      "1255  Episode Reward:  263.42437933788483 .Epsilon: 0.1\n",
      "1256  Episode Reward:  232.3461554080924 .Epsilon: 0.1\n",
      "1257  Episode Reward:  -251.59950264427093 .Epsilon: 0.1\n",
      "1258  Episode Reward:  236.39765004590197 .Epsilon: 0.1\n",
      "1259  Episode Reward:  -33.178755789486075 .Epsilon: 0.1\n",
      "1260  Episode Reward:  258.4807541067615 .Epsilon: 0.1\n",
      "1261  Episode Reward:  267.1621266267316 .Epsilon: 0.1\n",
      "1262  Episode Reward:  -97.71751138639463 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1263  Episode Reward:  253.24786417094225 .Epsilon: 0.1\n",
      "1264  Episode Reward:  -221.80136279268862 .Epsilon: 0.1\n",
      "1265  Episode Reward:  272.09460802492356 .Epsilon: 0.1\n",
      "1266  Episode Reward:  257.70579342558557 .Epsilon: 0.1\n",
      "1267  Episode Reward:  250.24869152298845 .Epsilon: 0.1\n",
      "1268  Episode Reward:  293.4526045660966 .Epsilon: 0.1\n",
      "1269  Episode Reward:  154.57603560362108 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1270  Episode Reward:  286.84287035168643 .Epsilon: 0.1\n",
      "1271  Episode Reward:  32.79885655955698 .Epsilon: 0.1\n",
      "1272  Episode Reward:  -126.90433933714405 .Epsilon: 0.1\n",
      "1273  Episode Reward:  31.280856291783948 .Epsilon: 0.1\n",
      "1274  Episode Reward:  247.07577171844076 .Epsilon: 0.1\n",
      "1275  Episode Reward:  -25.125697691981713 .Epsilon: 0.1\n",
      "1276  Episode Reward:  275.87802003470847 .Epsilon: 0.1\n",
      "1277  Episode Reward:  296.7806910526606 .Epsilon: 0.1\n",
      "1278  Episode Reward:  276.87801770952876 .Epsilon: 0.1\n",
      "1279  Episode Reward:  38.0237350091563 .Epsilon: 0.1\n",
      "1280  Episode Reward:  -158.44792711037107 .Epsilon: 0.1\n",
      "1281  Episode Reward:  -30.297549783835862 .Epsilon: 0.1\n",
      "1282  Episode Reward:  66.0230307330988 .Epsilon: 0.1\n",
      "1283  Episode Reward:  -48.939867575077734 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1284  Episode Reward:  262.6282939656187 .Epsilon: 0.1\n",
      "1285  Episode Reward:  -187.2577824527487 .Epsilon: 0.1\n",
      "1286  Episode Reward:  268.3920165621301 .Epsilon: 0.1\n",
      "1287  Episode Reward:  -21.652866320139935 .Epsilon: 0.1\n",
      "1288  Episode Reward:  29.12306416471023 .Epsilon: 0.1\n",
      "1289  Episode Reward:  59.617208424483664 .Epsilon: 0.1\n",
      "1290  Episode Reward:  299.21176405812867 .Epsilon: 0.1\n",
      "1291  Episode Reward:  292.66116674132184 .Epsilon: 0.1\n",
      "1292  Episode Reward:  227.65872874863416 .Epsilon: 0.1\n",
      "1293  Episode Reward:  -219.20945682679377 .Epsilon: 0.1\n",
      "1294  Episode Reward:  -203.2101097021451 .Epsilon: 0.1\n",
      "1295  Episode Reward:  256.5100479251201 .Epsilon: 0.1\n",
      "1296  Episode Reward:  12.016394844102848 .Epsilon: 0.1\n",
      "1297  Episode Reward:  38.070082598627124 .Epsilon: 0.1\n",
      "1298  Episode Reward:  -116.69898828921825 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1299  Episode Reward:  232.2184823830371 .Epsilon: 0.1\n",
      "1300  Episode Reward:  249.46534470864836 .Epsilon: 0.1\n",
      "1301  Episode Reward:  12.531819435284788 .Epsilon: 0.1\n",
      "1302  Episode Reward:  258.7719327847037 .Epsilon: 0.1\n",
      "1303  Episode Reward:  266.9351037520768 .Epsilon: 0.1\n",
      "1304  Episode Reward:  -113.6703273051916 .Epsilon: 0.1\n",
      "1305  Episode Reward:  259.2260478007235 .Epsilon: 0.1\n",
      "1306  Episode Reward:  57.68195139943839 .Epsilon: 0.1\n",
      "1307  Episode Reward:  -33.94467035376243 .Epsilon: 0.1\n",
      "1308  Episode Reward:  292.62075715187603 .Epsilon: 0.1\n",
      "1309  Episode Reward:  -25.631341046581 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1310  Episode Reward:  -137.000754587512 .Epsilon: 0.1\n",
      "1311  Episode Reward:  156.14251950089619 .Epsilon: 0.1\n",
      "1312  Episode Reward:  -52.196224052953056 .Epsilon: 0.1\n",
      "1313  Episode Reward:  21.089485921344163 .Epsilon: 0.1\n",
      "1314  Episode Reward:  254.35025951068363 .Epsilon: 0.1\n",
      "1315  Episode Reward:  256.8849567087949 .Epsilon: 0.1\n",
      "1316  Episode Reward:  174.6180844125986 .Epsilon: 0.1\n",
      "1317  Episode Reward:  23.91744571512291 .Epsilon: 0.1\n",
      "1318  Episode Reward:  251.34418921952525 .Epsilon: 0.1\n",
      "1319  Episode Reward:  -125.81452491635515 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1320  Episode Reward:  -0.39994861833149287 .Epsilon: 0.1\n",
      "1321  Episode Reward:  13.208851106219711 .Epsilon: 0.1\n",
      "1322  Episode Reward:  44.61260946517021 .Epsilon: 0.1\n",
      "1323  Episode Reward:  -176.63575598150408 .Epsilon: 0.1\n",
      "1324  Episode Reward:  262.4442158684559 .Epsilon: 0.1\n",
      "1325  Episode Reward:  -210.392197264088 .Epsilon: 0.1\n",
      "1326  Episode Reward:  0.9401811959095596 .Epsilon: 0.1\n",
      "1327  Episode Reward:  218.97846523595194 .Epsilon: 0.1\n",
      "1328  Episode Reward:  214.47175357000162 .Epsilon: 0.1\n",
      "1329  Episode Reward:  227.21823570346587 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1330  Episode Reward:  256.0335822127191 .Epsilon: 0.1\n",
      "1331  Episode Reward:  293.02642771843153 .Epsilon: 0.1\n",
      "1332  Episode Reward:  -232.12001620869293 .Epsilon: 0.1\n",
      "1333  Episode Reward:  269.61277052813114 .Epsilon: 0.1\n",
      "1334  Episode Reward:  -52.70126076249588 .Epsilon: 0.1\n",
      "1335  Episode Reward:  -110.34641894956108 .Epsilon: 0.1\n",
      "1336  Episode Reward:  251.5884825458769 .Epsilon: 0.1\n",
      "1337  Episode Reward:  -280.2945505829047 .Epsilon: 0.1\n",
      "1338  Episode Reward:  264.9357006643802 .Epsilon: 0.1\n",
      "1339  Episode Reward:  249.24299426411767 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1340  Episode Reward:  35.609002356225716 .Epsilon: 0.1\n",
      "1341  Episode Reward:  7.672484156360056 .Epsilon: 0.1\n",
      "1342  Episode Reward:  -169.79367898985842 .Epsilon: 0.1\n",
      "1343  Episode Reward:  124.55826353576438 .Epsilon: 0.1\n",
      "1344  Episode Reward:  23.248147831714647 .Epsilon: 0.1\n",
      "1345  Episode Reward:  245.27036114957545 .Epsilon: 0.1\n",
      "1346  Episode Reward:  264.6587774346453 .Epsilon: 0.1\n",
      "1347  Episode Reward:  24.27360237268161 .Epsilon: 0.1\n",
      "1348  Episode Reward:  -5.050980950950702 .Epsilon: 0.1\n",
      "1349  Episode Reward:  -21.87367018502549 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1350  Episode Reward:  242.28574012065056 .Epsilon: 0.1\n",
      "1351  Episode Reward:  265.2265285211257 .Epsilon: 0.1\n",
      "1352  Episode Reward:  -5.999666091297584 .Epsilon: 0.1\n",
      "1353  Episode Reward:  188.8169735469831 .Epsilon: 0.1\n",
      "1354  Episode Reward:  237.88135569923656 .Epsilon: 0.1\n",
      "1355  Episode Reward:  -272.0093245194627 .Epsilon: 0.1\n",
      "1356  Episode Reward:  253.6284783362725 .Epsilon: 0.1\n",
      "1357  Episode Reward:  -72.14264691633932 .Epsilon: 0.1\n",
      "1358  Episode Reward:  -60.51649339337634 .Epsilon: 0.1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "STATIC WEIGHTS UPDATED\n",
      "1359  Episode Reward:  261.6335479680688 .Epsilon: 0.1\n",
      "1360  Episode Reward:  162.4303230788051 .Epsilon: 0.1\n",
      "1361  Episode Reward:  262.1143540461059 .Epsilon: 0.1\n",
      "1362  Episode Reward:  -178.46751348337938 .Epsilon: 0.1\n",
      "1363  Episode Reward:  -171.47444913846996 .Epsilon: 0.1\n",
      "1364  Episode Reward:  25.734183011935315 .Epsilon: 0.1\n",
      "1365  Episode Reward:  -145.86315723310338 .Epsilon: 0.1\n",
      "1366  Episode Reward:  45.012479374781435 .Epsilon: 0.1\n",
      "1367  Episode Reward:  -261.0726554374324 .Epsilon: 0.1\n",
      "1368  Episode Reward:  14.854392619737993 .Epsilon: 0.1\n",
      "1369  Episode Reward:  36.26708146789639 .Epsilon: 0.1\n",
      "1370  Episode Reward:  0.5350832995605828 .Epsilon: 0.1\n",
      "1371  Episode Reward:  -86.09597546923301 .Epsilon: 0.1\n",
      "1372  Episode Reward:  213.59593478572444 .Epsilon: 0.1\n",
      "1373  Episode Reward:  -159.58572777298414 .Epsilon: 0.1\n",
      "1374  Episode Reward:  -321.19288086878163 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1375  Episode Reward:  275.4938440377133 .Epsilon: 0.1\n",
      "1376  Episode Reward:  38.38071785160835 .Epsilon: 0.1\n",
      "1377  Episode Reward:  267.33979894967393 .Epsilon: 0.1\n",
      "1378  Episode Reward:  -216.9635254627637 .Epsilon: 0.1\n",
      "1379  Episode Reward:  -97.27507143880305 .Epsilon: 0.1\n",
      "1380  Episode Reward:  12.910838194269274 .Epsilon: 0.1\n",
      "1381  Episode Reward:  258.3942718338221 .Epsilon: 0.1\n",
      "1382  Episode Reward:  4.707505046596296 .Epsilon: 0.1\n",
      "1383  Episode Reward:  257.195740636642 .Epsilon: 0.1\n",
      "1384  Episode Reward:  291.9610016835072 .Epsilon: 0.1\n",
      "1385  Episode Reward:  -176.43316676646054 .Epsilon: 0.1\n",
      "1386  Episode Reward:  241.73939210108287 .Epsilon: 0.1\n",
      "1387  Episode Reward:  -19.217584961383395 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1388  Episode Reward:  258.04414521437513 .Epsilon: 0.1\n",
      "1389  Episode Reward:  166.63037593416158 .Epsilon: 0.1\n",
      "1390  Episode Reward:  -91.83599010612721 .Epsilon: 0.1\n",
      "1391  Episode Reward:  -163.56973073274145 .Epsilon: 0.1\n",
      "1392  Episode Reward:  264.801590388007 .Epsilon: 0.1\n",
      "1393  Episode Reward:  -124.65124825102234 .Epsilon: 0.1\n",
      "1394  Episode Reward:  24.588670842706463 .Epsilon: 0.1\n",
      "1395  Episode Reward:  39.8662697126598 .Epsilon: 0.1\n",
      "1396  Episode Reward:  258.0685453192249 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1397  Episode Reward:  -162.46824211066362 .Epsilon: 0.1\n",
      "1398  Episode Reward:  -6.004039999280167 .Epsilon: 0.1\n",
      "1399  Episode Reward:  277.60616847214703 .Epsilon: 0.1\n",
      "1400  Episode Reward:  200.81410552293707 .Epsilon: 0.1\n",
      "1401  Episode Reward:  41.59064214667313 .Epsilon: 0.1\n",
      "1402  Episode Reward:  22.153608253533676 .Epsilon: 0.1\n",
      "1403  Episode Reward:  -284.4186086658893 .Epsilon: 0.1\n",
      "1404  Episode Reward:  255.44085839466152 .Epsilon: 0.1\n",
      "1405  Episode Reward:  40.21741602815254 .Epsilon: 0.1\n",
      "1406  Episode Reward:  -243.51623150324858 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1407  Episode Reward:  273.68418604757403 .Epsilon: 0.1\n",
      "1408  Episode Reward:  29.754553915978818 .Epsilon: 0.1\n",
      "1409  Episode Reward:  276.1146861115924 .Epsilon: 0.1\n",
      "1410  Episode Reward:  -147.98960583631688 .Epsilon: 0.1\n",
      "1411  Episode Reward:  273.56011539065184 .Epsilon: 0.1\n",
      "1412  Episode Reward:  -157.29124240247694 .Epsilon: 0.1\n",
      "1413  Episode Reward:  245.14838372789973 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1414  Episode Reward:  203.75450938706882 .Epsilon: 0.1\n",
      "1415  Episode Reward:  -104.75944047819466 .Epsilon: 0.1\n",
      "1416  Episode Reward:  242.2848448919612 .Epsilon: 0.1\n",
      "1417  Episode Reward:  -305.64578078406583 .Epsilon: 0.1\n",
      "1418  Episode Reward:  267.57064594216456 .Epsilon: 0.1\n",
      "1419  Episode Reward:  122.97448265917672 .Epsilon: 0.1\n",
      "1420  Episode Reward:  40.924934429930914 .Epsilon: 0.1\n",
      "1421  Episode Reward:  301.2016153210752 .Epsilon: 0.1\n",
      "1422  Episode Reward:  -269.08797943252665 .Epsilon: 0.1\n",
      "1423  Episode Reward:  32.51886072096397 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1424  Episode Reward:  143.92299244301762 .Epsilon: 0.1\n",
      "1425  Episode Reward:  254.12903111001685 .Epsilon: 0.1\n",
      "1426  Episode Reward:  238.04192917913298 .Epsilon: 0.1\n",
      "1427  Episode Reward:  245.12355314116434 .Epsilon: 0.1\n",
      "1428  Episode Reward:  250.47155906547835 .Epsilon: 0.1\n",
      "1429  Episode Reward:  -127.06651446819403 .Epsilon: 0.1\n",
      "1430  Episode Reward:  196.8193846852676 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1431  Episode Reward:  180.56059525231655 .Epsilon: 0.1\n",
      "1432  Episode Reward:  284.94439411680094 .Epsilon: 0.1\n",
      "1433  Episode Reward:  232.64909331309738 .Epsilon: 0.1\n",
      "1434  Episode Reward:  -149.22407960810136 .Epsilon: 0.1\n",
      "1435  Episode Reward:  237.85533499602698 .Epsilon: 0.1\n",
      "1436  Episode Reward:  38.197036623901425 .Epsilon: 0.1\n",
      "1437  Episode Reward:  -180.9697298571905 .Epsilon: 0.1\n",
      "1438  Episode Reward:  263.58608095695035 .Epsilon: 0.1\n",
      "1439  Episode Reward:  199.52567579496488 .Epsilon: 0.1\n",
      "1440  Episode Reward:  10.871634748443526 .Epsilon: 0.1\n",
      "1441  Episode Reward:  249.066236349388 .Epsilon: 0.1\n",
      "1442  Episode Reward:  15.49471325263059 .Epsilon: 0.1\n",
      "1443  Episode Reward:  -34.18980554885833 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1444  Episode Reward:  288.53181346062144 .Epsilon: 0.1\n",
      "1445  Episode Reward:  -283.231818176169 .Epsilon: 0.1\n",
      "1446  Episode Reward:  254.5011807804085 .Epsilon: 0.1\n",
      "1447  Episode Reward:  292.5012818869309 .Epsilon: 0.1\n",
      "1448  Episode Reward:  199.15671612294057 .Epsilon: 0.1\n",
      "1449  Episode Reward:  -23.565933564983396 .Epsilon: 0.1\n",
      "1450  Episode Reward:  249.0188645721797 .Epsilon: 0.1\n",
      "1451  Episode Reward:  -170.7769396704433 .Epsilon: 0.1\n",
      "1452  Episode Reward:  258.9287074735915 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1453  Episode Reward:  17.58180264104115 .Epsilon: 0.1\n",
      "1454  Episode Reward:  43.17937171494373 .Epsilon: 0.1\n",
      "1455  Episode Reward:  229.9515856388119 .Epsilon: 0.1\n",
      "1456  Episode Reward:  131.37992121084412 .Epsilon: 0.1\n",
      "1457  Episode Reward:  254.49096495521496 .Epsilon: 0.1\n",
      "1458  Episode Reward:  -263.7558627372139 .Epsilon: 0.1\n",
      "1459  Episode Reward:  231.34706833063362 .Epsilon: 0.1\n",
      "1460  Episode Reward:  221.21292891716718 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1461  Episode Reward:  -38.64054481112646 .Epsilon: 0.1\n",
      "1462  Episode Reward:  276.5677054468556 .Epsilon: 0.1\n",
      "1463  Episode Reward:  247.57387234910095 .Epsilon: 0.1\n",
      "1464  Episode Reward:  276.20514752337874 .Epsilon: 0.1\n",
      "1465  Episode Reward:  291.2129637463333 .Epsilon: 0.1\n",
      "1466  Episode Reward:  294.3684395982708 .Epsilon: 0.1\n",
      "1467  Episode Reward:  21.071428707180047 .Epsilon: 0.1\n",
      "1468  Episode Reward:  258.37710540838833 .Epsilon: 0.1\n",
      "1469  Episode Reward:  -214.6984997873205 .Epsilon: 0.1\n",
      "1470  Episode Reward:  258.46703329598154 .Epsilon: 0.1\n",
      "1471  Episode Reward:  263.0845764237885 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1472  Episode Reward:  -164.34079465118748 .Epsilon: 0.1\n",
      "1473  Episode Reward:  11.230711216902606 .Epsilon: 0.1\n",
      "1474  Episode Reward:  -153.18609407249483 .Epsilon: 0.1\n",
      "1475  Episode Reward:  -349.10120186644554 .Epsilon: 0.1\n",
      "1476  Episode Reward:  264.01459622035077 .Epsilon: 0.1\n",
      "1477  Episode Reward:  269.6750815989668 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1478  Episode Reward:  -259.25297353342097 .Epsilon: 0.1\n",
      "1479  Episode Reward:  292.52403871753165 .Epsilon: 0.1\n",
      "1480  Episode Reward:  39.99376856181058 .Epsilon: 0.1\n",
      "1481  Episode Reward:  227.91867412933917 .Epsilon: 0.1\n",
      "1482  Episode Reward:  207.5492603770765 .Epsilon: 0.1\n",
      "1483  Episode Reward:  -188.67620140620014 .Epsilon: 0.1\n",
      "1484  Episode Reward:  -353.61752487825015 .Epsilon: 0.1\n",
      "1485  Episode Reward:  -226.74042567564368 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1486  Episode Reward:  -45.86849571351841 .Epsilon: 0.1\n",
      "1487  Episode Reward:  39.163138498993334 .Epsilon: 0.1\n",
      "1488  Episode Reward:  257.1677758242838 .Epsilon: 0.1\n",
      "1489  Episode Reward:  -0.978686173684153 .Epsilon: 0.1\n",
      "1490  Episode Reward:  37.59061752665424 .Epsilon: 0.1\n",
      "1491  Episode Reward:  265.7500999195378 .Epsilon: 0.1\n",
      "1492  Episode Reward:  -134.86409096778124 .Epsilon: 0.1\n",
      "1493  Episode Reward:  273.2464641457336 .Epsilon: 0.1\n",
      "1494  Episode Reward:  274.6310628654296 .Epsilon: 0.1\n",
      "1495  Episode Reward:  268.9362695161058 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1496  Episode Reward:  256.60060090376567 .Epsilon: 0.1\n",
      "1497  Episode Reward:  238.83187289441565 .Epsilon: 0.1\n",
      "1498  Episode Reward:  43.35568588909953 .Epsilon: 0.1\n",
      "1499  Episode Reward:  -4.087081690513159 .Epsilon: 0.1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1500  Episode Reward:  246.68332935902356 .Epsilon: 0.1\n",
      "1501  Episode Reward:  -5.128544665069725 .Epsilon: 0.1\n",
      "1502  Episode Reward:  239.03990635196763 .Epsilon: 0.1\n",
      "1503  Episode Reward:  244.1682520177093 .Epsilon: 0.1\n",
      "1504  Episode Reward:  285.04078645415984 .Epsilon: 0.1\n",
      "1505  Episode Reward:  236.16543015729755 .Epsilon: 0.1\n",
      "1506  Episode Reward:  295.2045501042083 .Epsilon: 0.1\n",
      "1507  Episode Reward:  260.07084101257664 .Epsilon: 0.1\n",
      "1508  Episode Reward:  272.45475964983973 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1509  Episode Reward:  -114.85208159100773 .Epsilon: 0.1\n",
      "1510  Episode Reward:  261.5100392966534 .Epsilon: 0.1\n",
      "1511  Episode Reward:  249.6545064071451 .Epsilon: 0.1\n",
      "1512  Episode Reward:  -4.423008791166069 .Epsilon: 0.1\n",
      "1513  Episode Reward:  231.51354203814157 .Epsilon: 0.1\n",
      "1514  Episode Reward:  5.375056345090741 .Epsilon: 0.1\n",
      "1515  Episode Reward:  280.7388899635371 .Epsilon: 0.1\n",
      "1516  Episode Reward:  267.1482817897795 .Epsilon: 0.1\n",
      "1517  Episode Reward:  251.75354334720106 .Epsilon: 0.1\n",
      "1518  Episode Reward:  19.962019525039267 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1519  Episode Reward:  -249.26761390921916 .Epsilon: 0.1\n",
      "1520  Episode Reward:  292.4963582802684 .Epsilon: 0.1\n",
      "1521  Episode Reward:  241.32077623990267 .Epsilon: 0.1\n",
      "1522  Episode Reward:  274.38842287916395 .Epsilon: 0.1\n",
      "1523  Episode Reward:  202.61494103541307 .Epsilon: 0.1\n",
      "1524  Episode Reward:  -5.259724390366671 .Epsilon: 0.1\n",
      "1525  Episode Reward:  277.0348362799291 .Epsilon: 0.1\n",
      "1526  Episode Reward:  228.52266380975695 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1527  Episode Reward:  259.8765806831752 .Epsilon: 0.1\n",
      "1528  Episode Reward:  279.447031693918 .Epsilon: 0.1\n",
      "1529  Episode Reward:  -114.24655153793158 .Epsilon: 0.1\n",
      "1530  Episode Reward:  303.48685196378557 .Epsilon: 0.1\n",
      "1531  Episode Reward:  -140.2121461720127 .Epsilon: 0.1\n",
      "1532  Episode Reward:  261.8244975824241 .Epsilon: 0.1\n",
      "1533  Episode Reward:  12.733081214333476 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1534  Episode Reward:  268.99249325784746 .Epsilon: 0.1\n",
      "1535  Episode Reward:  -192.51346455838234 .Epsilon: 0.1\n",
      "1536  Episode Reward:  299.6359245801633 .Epsilon: 0.1\n",
      "1537  Episode Reward:  304.0900725312769 .Epsilon: 0.1\n",
      "1538  Episode Reward:  229.91259405167133 .Epsilon: 0.1\n",
      "1539  Episode Reward:  -17.586595719955866 .Epsilon: 0.1\n",
      "1540  Episode Reward:  -229.70784813323442 .Epsilon: 0.1\n",
      "1541  Episode Reward:  233.9057597618357 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1542  Episode Reward:  27.31666004427379 .Epsilon: 0.1\n",
      "1543  Episode Reward:  236.28720276459086 .Epsilon: 0.1\n",
      "1544  Episode Reward:  262.9532735825409 .Epsilon: 0.1\n",
      "1545  Episode Reward:  232.18691277107573 .Epsilon: 0.1\n",
      "1546  Episode Reward:  -132.7651262890356 .Epsilon: 0.1\n",
      "1547  Episode Reward:  280.05970429403624 .Epsilon: 0.1\n",
      "1548  Episode Reward:  277.92514864109154 .Epsilon: 0.1\n",
      "1549  Episode Reward:  -195.06568306255372 .Epsilon: 0.1\n",
      "1550  Episode Reward:  259.7272320200608 .Epsilon: 0.1\n",
      "1551  Episode Reward:  261.53751339841455 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1552  Episode Reward:  274.86852736310345 .Epsilon: 0.1\n",
      "1553  Episode Reward:  -241.66336063093223 .Epsilon: 0.1\n",
      "1554  Episode Reward:  -12.514749650883445 .Epsilon: 0.1\n",
      "1555  Episode Reward:  12.682994623421152 .Epsilon: 0.1\n",
      "1556  Episode Reward:  262.0017156865629 .Epsilon: 0.1\n",
      "1557  Episode Reward:  250.02130686939725 .Epsilon: 0.1\n",
      "1558  Episode Reward:  227.83766134103772 .Epsilon: 0.1\n",
      "1559  Episode Reward:  244.42767483273505 .Epsilon: 0.1\n",
      "1560  Episode Reward:  284.48966452871264 .Epsilon: 0.1\n",
      "1561  Episode Reward:  267.0027110463233 .Epsilon: 0.1\n",
      "1562  Episode Reward:  -393.3487923955623 .Epsilon: 0.1\n",
      "1563  Episode Reward:  -248.7022820197572 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1564  Episode Reward:  267.87065578907675 .Epsilon: 0.1\n",
      "1565  Episode Reward:  254.78657896378215 .Epsilon: 0.1\n",
      "1566  Episode Reward:  110.82030592077344 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1567  Episode Reward:  238.0274603377065 .Epsilon: 0.1\n",
      "1568  Episode Reward:  277.87685951439505 .Epsilon: 0.1\n",
      "1569  Episode Reward:  232.22530967909978 .Epsilon: 0.1\n",
      "1570  Episode Reward:  261.96509180587196 .Epsilon: 0.1\n",
      "1571  Episode Reward:  245.89612478527374 .Epsilon: 0.1\n",
      "1572  Episode Reward:  -9.356469424492104 .Epsilon: 0.1\n",
      "1573  Episode Reward:  230.24809747604962 .Epsilon: 0.1\n",
      "1574  Episode Reward:  -253.35174372716153 .Epsilon: 0.1\n",
      "1575  Episode Reward:  239.98280537030604 .Epsilon: 0.1\n",
      "1576  Episode Reward:  244.57342876493178 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1577  Episode Reward:  236.78363369068705 .Epsilon: 0.1\n",
      "1578  Episode Reward:  266.75324792011935 .Epsilon: 0.1\n",
      "1579  Episode Reward:  286.601417597936 .Epsilon: 0.1\n",
      "1580  Episode Reward:  257.8106116108873 .Epsilon: 0.1\n",
      "1581  Episode Reward:  271.64164034096615 .Epsilon: 0.1\n",
      "1582  Episode Reward:  -46.260818772832124 .Epsilon: 0.1\n",
      "1583  Episode Reward:  276.6267581420649 .Epsilon: 0.1\n",
      "1584  Episode Reward:  278.07143290762247 .Epsilon: 0.1\n",
      "1585  Episode Reward:  270.83492411691645 .Epsilon: 0.1\n",
      "1586  Episode Reward:  249.98833435663335 .Epsilon: 0.1\n",
      "1587  Episode Reward:  258.57506927564054 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1588  Episode Reward:  253.72042195901437 .Epsilon: 0.1\n",
      "1589  Episode Reward:  287.051001156828 .Epsilon: 0.1\n",
      "1590  Episode Reward:  279.67537622739576 .Epsilon: 0.1\n",
      "1591  Episode Reward:  285.9295867228443 .Epsilon: 0.1\n",
      "1592  Episode Reward:  152.21808295472096 .Epsilon: 0.1\n",
      "1593  Episode Reward:  244.4208161840295 .Epsilon: 0.1\n",
      "1594  Episode Reward:  43.327456334365536 .Epsilon: 0.1\n",
      "1595  Episode Reward:  281.3487839832712 .Epsilon: 0.1\n",
      "1596  Episode Reward:  20.03162073081272 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1597  Episode Reward:  -304.0800781383877 .Epsilon: 0.1\n",
      "1598  Episode Reward:  273.3397696816478 .Epsilon: 0.1\n",
      "1599  Episode Reward:  -99.73423178128141 .Epsilon: 0.1\n",
      "1600  Episode Reward:  289.8374032868744 .Epsilon: 0.1\n",
      "1601  Episode Reward:  241.85611306913773 .Epsilon: 0.1\n",
      "1602  Episode Reward:  259.8550329063922 .Epsilon: 0.1\n",
      "1603  Episode Reward:  271.3044050979951 .Epsilon: 0.1\n",
      "1604  Episode Reward:  264.6173565267384 .Epsilon: 0.1\n",
      "1605  Episode Reward:  271.20811154254443 .Epsilon: 0.1\n",
      "1606  Episode Reward:  298.4844741773475 .Epsilon: 0.1\n",
      "1607  Episode Reward:  -157.5688509213631 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1608  Episode Reward:  136.61738581713436 .Epsilon: 0.1\n",
      "1609  Episode Reward:  -129.85024345501802 .Epsilon: 0.1\n",
      "1610  Episode Reward:  266.91401757898007 .Epsilon: 0.1\n",
      "1611  Episode Reward:  213.3080460123544 .Epsilon: 0.1\n",
      "1612  Episode Reward:  -142.38321678939732 .Epsilon: 0.1\n",
      "1613  Episode Reward:  156.38445487299427 .Epsilon: 0.1\n",
      "1614  Episode Reward:  -3.291701356797887 .Epsilon: 0.1\n",
      "1615  Episode Reward:  286.90087495825617 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1616  Episode Reward:  90.9634488042851 .Epsilon: 0.1\n",
      "1617  Episode Reward:  241.2798494919965 .Epsilon: 0.1\n",
      "1618  Episode Reward:  -19.393049641114587 .Epsilon: 0.1\n",
      "1619  Episode Reward:  -76.26700478663273 .Epsilon: 0.1\n",
      "1620  Episode Reward:  -79.60169347527534 .Epsilon: 0.1\n",
      "1621  Episode Reward:  215.67686744182885 .Epsilon: 0.1\n",
      "1622  Episode Reward:  -39.019667945763274 .Epsilon: 0.1\n",
      "1623  Episode Reward:  227.84198276031032 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1624  Episode Reward:  -243.47814559941952 .Epsilon: 0.1\n",
      "1625  Episode Reward:  264.6216123661228 .Epsilon: 0.1\n",
      "1626  Episode Reward:  276.4507558153648 .Epsilon: 0.1\n",
      "1627  Episode Reward:  251.17452220903138 .Epsilon: 0.1\n",
      "1628  Episode Reward:  -81.10634236410147 .Epsilon: 0.1\n",
      "1629  Episode Reward:  273.113886263312 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1630  Episode Reward:  205.70782047009703 .Epsilon: 0.1\n",
      "1631  Episode Reward:  88.66450870309532 .Epsilon: 0.1\n",
      "1632  Episode Reward:  8.339340618088585 .Epsilon: 0.1\n",
      "1633  Episode Reward:  238.43533647258903 .Epsilon: 0.1\n",
      "1634  Episode Reward:  248.64504753098902 .Epsilon: 0.1\n",
      "1635  Episode Reward:  -13.989899541113843 .Epsilon: 0.1\n",
      "1636  Episode Reward:  -238.92882653044074 .Epsilon: 0.1\n",
      "1637  Episode Reward:  268.6826925407694 .Epsilon: 0.1\n",
      "1638  Episode Reward:  285.0918280658118 .Epsilon: 0.1\n",
      "1639  Episode Reward:  -3.3773812160157917 .Epsilon: 0.1\n",
      "1640  Episode Reward:  295.77637085269936 .Epsilon: 0.1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "STATIC WEIGHTS UPDATED\n",
      "1641  Episode Reward:  -293.0472088835095 .Epsilon: 0.1\n",
      "1642  Episode Reward:  254.7459117079398 .Epsilon: 0.1\n",
      "1643  Episode Reward:  273.0392072725314 .Epsilon: 0.1\n",
      "1644  Episode Reward:  258.5336706700429 .Epsilon: 0.1\n",
      "1645  Episode Reward:  12.275974146040838 .Epsilon: 0.1\n",
      "1646  Episode Reward:  282.66693595275564 .Epsilon: 0.1\n",
      "1647  Episode Reward:  237.60520021056234 .Epsilon: 0.1\n",
      "1648  Episode Reward:  19.291147521921786 .Epsilon: 0.1\n",
      "1649  Episode Reward:  -33.9907129188299 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1650  Episode Reward:  -237.6886867117075 .Epsilon: 0.1\n",
      "1651  Episode Reward:  285.15847467663286 .Epsilon: 0.1\n",
      "1652  Episode Reward:  270.62546813551427 .Epsilon: 0.1\n",
      "1653  Episode Reward:  253.33160112293953 .Epsilon: 0.1\n",
      "1654  Episode Reward:  256.3659307732576 .Epsilon: 0.1\n",
      "1655  Episode Reward:  293.4692158189305 .Epsilon: 0.1\n",
      "1656  Episode Reward:  291.1156096500001 .Epsilon: 0.1\n",
      "1657  Episode Reward:  251.88825479648747 .Epsilon: 0.1\n",
      "1658  Episode Reward:  256.73104083223177 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1659  Episode Reward:  206.71894025183153 .Epsilon: 0.1\n",
      "1660  Episode Reward:  168.2754372046557 .Epsilon: 0.1\n",
      "1661  Episode Reward:  -196.47039282713706 .Epsilon: 0.1\n",
      "1662  Episode Reward:  242.2212194549764 .Epsilon: 0.1\n",
      "1663  Episode Reward:  274.462323285328 .Epsilon: 0.1\n",
      "1664  Episode Reward:  36.43729182945327 .Epsilon: 0.1\n",
      "1665  Episode Reward:  254.33994562832788 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1666  Episode Reward:  254.67789669590928 .Epsilon: 0.1\n",
      "1667  Episode Reward:  -2.914193185703482 .Epsilon: 0.1\n",
      "1668  Episode Reward:  300.1907471184569 .Epsilon: 0.1\n",
      "1669  Episode Reward:  246.8536885209588 .Epsilon: 0.1\n",
      "1670  Episode Reward:  278.23203057706985 .Epsilon: 0.1\n",
      "1671  Episode Reward:  41.86948938322786 .Epsilon: 0.1\n",
      "1672  Episode Reward:  254.8853754225388 .Epsilon: 0.1\n",
      "1673  Episode Reward:  280.3604195857087 .Epsilon: 0.1\n",
      "1674  Episode Reward:  176.04758190234548 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1675  Episode Reward:  115.4977311542998 .Epsilon: 0.1\n",
      "1676  Episode Reward:  264.3508875022732 .Epsilon: 0.1\n",
      "1677  Episode Reward:  -19.414125262026545 .Epsilon: 0.1\n",
      "1678  Episode Reward:  285.385900325164 .Epsilon: 0.1\n",
      "1679  Episode Reward:  10.798398549952623 .Epsilon: 0.1\n",
      "1680  Episode Reward:  231.11330976802404 .Epsilon: 0.1\n",
      "1681  Episode Reward:  281.20064962714173 .Epsilon: 0.1\n",
      "1682  Episode Reward:  248.73656366152642 .Epsilon: 0.1\n",
      "1683  Episode Reward:  288.55525785353825 .Epsilon: 0.1\n",
      "1684  Episode Reward:  269.8881557317883 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1685  Episode Reward:  -6.692591970331691 .Epsilon: 0.1\n",
      "1686  Episode Reward:  63.7999316679074 .Epsilon: 0.1\n",
      "1687  Episode Reward:  18.95734619511593 .Epsilon: 0.1\n",
      "1688  Episode Reward:  247.90368680518307 .Epsilon: 0.1\n",
      "1689  Episode Reward:  24.22112281959349 .Epsilon: 0.1\n",
      "1690  Episode Reward:  289.2466245511715 .Epsilon: 0.1\n",
      "1691  Episode Reward:  273.9528028605574 .Epsilon: 0.1\n",
      "1692  Episode Reward:  -143.9523816141317 .Epsilon: 0.1\n",
      "1693  Episode Reward:  -3.1940501258768705 .Epsilon: 0.1\n",
      "1694  Episode Reward:  -59.961604099233455 .Epsilon: 0.1\n",
      "1695  Episode Reward:  119.75230882337398 .Epsilon: 0.1\n",
      "1696  Episode Reward:  262.38997590051855 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1697  Episode Reward:  264.88370836629394 .Epsilon: 0.1\n",
      "1698  Episode Reward:  278.5371427625482 .Epsilon: 0.1\n",
      "1699  Episode Reward:  283.01490248866423 .Epsilon: 0.1\n",
      "1700  Episode Reward:  248.78443403303942 .Epsilon: 0.1\n",
      "1701  Episode Reward:  257.29496640616867 .Epsilon: 0.1\n",
      "1702  Episode Reward:  -126.31384525392554 .Epsilon: 0.1\n",
      "1703  Episode Reward:  288.0897839462864 .Epsilon: 0.1\n",
      "1704  Episode Reward:  263.5902405918981 .Epsilon: 0.1\n",
      "1705  Episode Reward:  267.0758097350834 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1706  Episode Reward:  103.81343719555205 .Epsilon: 0.1\n",
      "1707  Episode Reward:  -42.893719994444425 .Epsilon: 0.1\n",
      "1708  Episode Reward:  -37.05177897142515 .Epsilon: 0.1\n",
      "1709  Episode Reward:  268.68812347666875 .Epsilon: 0.1\n",
      "1710  Episode Reward:  268.3927242374594 .Epsilon: 0.1\n",
      "1711  Episode Reward:  285.74743647307656 .Epsilon: 0.1\n",
      "1712  Episode Reward:  138.42035492483106 .Epsilon: 0.1\n",
      "1713  Episode Reward:  257.24179176721236 .Epsilon: 0.1\n",
      "1714  Episode Reward:  271.43578349087255 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1715  Episode Reward:  227.01358488447093 .Epsilon: 0.1\n",
      "1716  Episode Reward:  -272.4982014186021 .Epsilon: 0.1\n",
      "1717  Episode Reward:  264.2566716051475 .Epsilon: 0.1\n",
      "1718  Episode Reward:  -157.14336627984866 .Epsilon: 0.1\n",
      "1719  Episode Reward:  245.20924376449037 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1720  Episode Reward:  -211.57552672433127 .Epsilon: 0.1\n",
      "1721  Episode Reward:  10.824566176989563 .Epsilon: 0.1\n",
      "1722  Episode Reward:  -36.90169174823238 .Epsilon: 0.1\n",
      "1723  Episode Reward:  281.87100182124595 .Epsilon: 0.1\n",
      "1724  Episode Reward:  38.36546304810969 .Epsilon: 0.1\n",
      "1725  Episode Reward:  263.6870744767258 .Epsilon: 0.1\n",
      "1726  Episode Reward:  276.32192843029054 .Epsilon: 0.1\n",
      "1727  Episode Reward:  254.4616450719459 .Epsilon: 0.1\n",
      "1728  Episode Reward:  -227.94711083714833 .Epsilon: 0.1\n",
      "1729  Episode Reward:  260.2634999768188 .Epsilon: 0.1\n",
      "1730  Episode Reward:  -278.5568789669426 .Epsilon: 0.1\n",
      "1731  Episode Reward:  -360.5724065966288 .Epsilon: 0.1\n",
      "1732  Episode Reward:  260.5520150903659 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1733  Episode Reward:  271.7267132968723 .Epsilon: 0.1\n",
      "1734  Episode Reward:  306.93252460773886 .Epsilon: 0.1\n",
      "1735  Episode Reward:  -84.88014666878794 .Epsilon: 0.1\n",
      "1736  Episode Reward:  44.24067655586251 .Epsilon: 0.1\n",
      "1737  Episode Reward:  -427.4227627473728 .Epsilon: 0.1\n",
      "1738  Episode Reward:  245.9047910714671 .Epsilon: 0.1\n",
      "1739  Episode Reward:  278.19194302619997 .Epsilon: 0.1\n",
      "1740  Episode Reward:  256.70617245060214 .Epsilon: 0.1\n",
      "1741  Episode Reward:  268.74768915412676 .Epsilon: 0.1\n",
      "1742  Episode Reward:  10.355273132528424 .Epsilon: 0.1\n",
      "1743  Episode Reward:  242.2417757778977 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1744  Episode Reward:  101.28229452802094 .Epsilon: 0.1\n",
      "1745  Episode Reward:  193.63064730352238 .Epsilon: 0.1\n",
      "1746  Episode Reward:  211.4419567935936 .Epsilon: 0.1\n",
      "1747  Episode Reward:  278.96422095118453 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1748  Episode Reward:  73.74079837572461 .Epsilon: 0.1\n",
      "1749  Episode Reward:  29.355566293873835 .Epsilon: 0.1\n",
      "1750  Episode Reward:  286.6214257216433 .Epsilon: 0.1\n",
      "1751  Episode Reward:  -323.00732859363916 .Epsilon: 0.1\n",
      "1752  Episode Reward:  261.0620229411728 .Epsilon: 0.1\n",
      "1753  Episode Reward:  284.2690042512679 .Epsilon: 0.1\n",
      "1754  Episode Reward:  240.5123933703008 .Epsilon: 0.1\n",
      "1755  Episode Reward:  -377.3593691875516 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1756  Episode Reward:  264.74733091554367 .Epsilon: 0.1\n",
      "1757  Episode Reward:  -6.547293448177868 .Epsilon: 0.1\n",
      "1758  Episode Reward:  234.2293883202334 .Epsilon: 0.1\n",
      "1759  Episode Reward:  241.35800150133733 .Epsilon: 0.1\n",
      "1760  Episode Reward:  -211.1568678498773 .Epsilon: 0.1\n",
      "1761  Episode Reward:  256.2248421922528 .Epsilon: 0.1\n",
      "1762  Episode Reward:  275.0950167785036 .Epsilon: 0.1\n",
      "1763  Episode Reward:  29.97984058366916 .Epsilon: 0.1\n",
      "1764  Episode Reward:  279.8216107479734 .Epsilon: 0.1\n",
      "1765  Episode Reward:  289.1667721164257 .Epsilon: 0.1\n",
      "1766  Episode Reward:  247.0300070711753 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1767  Episode Reward:  226.08084293890067 .Epsilon: 0.1\n",
      "1768  Episode Reward:  193.903862827767 .Epsilon: 0.1\n",
      "1769  Episode Reward:  249.77017800040122 .Epsilon: 0.1\n",
      "1770  Episode Reward:  21.322672757461007 .Epsilon: 0.1\n",
      "1771  Episode Reward:  -13.010320333879122 .Epsilon: 0.1\n",
      "1772  Episode Reward:  258.41258200885204 .Epsilon: 0.1\n",
      "1773  Episode Reward:  19.78764654686779 .Epsilon: 0.1\n",
      "1774  Episode Reward:  250.56914894752938 .Epsilon: 0.1\n",
      "1775  Episode Reward:  279.71437090645384 .Epsilon: 0.1\n",
      "1776  Episode Reward:  13.870778035555261 .Epsilon: 0.1\n",
      "1777  Episode Reward:  -46.47723535573971 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1778  Episode Reward:  283.7435476652463 .Epsilon: 0.1\n",
      "1779  Episode Reward:  -189.18785044999416 .Epsilon: 0.1\n",
      "1780  Episode Reward:  48.366287327107926 .Epsilon: 0.1\n",
      "1781  Episode Reward:  268.2624195437246 .Epsilon: 0.1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1782  Episode Reward:  -150.3914409558448 .Epsilon: 0.1\n",
      "1783  Episode Reward:  269.5669404843359 .Epsilon: 0.1\n",
      "1784  Episode Reward:  258.91419732052435 .Epsilon: 0.1\n",
      "1785  Episode Reward:  283.05263275815275 .Epsilon: 0.1\n",
      "1786  Episode Reward:  239.97651079423437 .Epsilon: 0.1\n",
      "1787  Episode Reward:  13.843699838752173 .Epsilon: 0.1\n",
      "1788  Episode Reward:  278.95061619552905 .Epsilon: 0.1\n",
      "1789  Episode Reward:  253.60334818858917 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1790  Episode Reward:  224.97940144122316 .Epsilon: 0.1\n",
      "1791  Episode Reward:  269.57976020944363 .Epsilon: 0.1\n",
      "1792  Episode Reward:  283.8282621008457 .Epsilon: 0.1\n",
      "1793  Episode Reward:  233.02254665925173 .Epsilon: 0.1\n",
      "1794  Episode Reward:  123.02720250800772 .Epsilon: 0.1\n",
      "1795  Episode Reward:  41.29182229740536 .Epsilon: 0.1\n",
      "1796  Episode Reward:  30.3892129907465 .Epsilon: 0.1\n",
      "1797  Episode Reward:  -13.050892306931345 .Epsilon: 0.1\n",
      "1798  Episode Reward:  258.629547326874 .Epsilon: 0.1\n",
      "1799  Episode Reward:  25.555595463468833 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1800  Episode Reward:  11.10037038990555 .Epsilon: 0.1\n",
      "1801  Episode Reward:  -3.0558431550240357 .Epsilon: 0.1\n",
      "1802  Episode Reward:  -11.674324844467023 .Epsilon: 0.1\n",
      "1803  Episode Reward:  -13.846638914396692 .Epsilon: 0.1\n",
      "1804  Episode Reward:  58.96613579088404 .Epsilon: 0.1\n",
      "1805  Episode Reward:  255.86370991571965 .Epsilon: 0.1\n",
      "1806  Episode Reward:  -198.24780580186342 .Epsilon: 0.1\n",
      "1807  Episode Reward:  269.19155544892374 .Epsilon: 0.1\n",
      "1808  Episode Reward:  268.0291329007609 .Epsilon: 0.1\n",
      "1809  Episode Reward:  -391.91435880726016 .Epsilon: 0.1\n",
      "1810  Episode Reward:  265.4300166974539 .Epsilon: 0.1\n",
      "1811  Episode Reward:  257.61779961686824 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1812  Episode Reward:  -51.13163435049354 .Epsilon: 0.1\n",
      "1813  Episode Reward:  -10.299373707776795 .Epsilon: 0.1\n",
      "1814  Episode Reward:  266.7664266304772 .Epsilon: 0.1\n",
      "1815  Episode Reward:  -109.79635211978992 .Epsilon: 0.1\n",
      "1816  Episode Reward:  276.29914268735763 .Epsilon: 0.1\n",
      "1817  Episode Reward:  -245.4009093067637 .Epsilon: 0.1\n",
      "1818  Episode Reward:  270.7459165087507 .Epsilon: 0.1\n",
      "1819  Episode Reward:  293.47303463163996 .Epsilon: 0.1\n",
      "1820  Episode Reward:  185.37701158806397 .Epsilon: 0.1\n",
      "1821  Episode Reward:  256.37741502992856 .Epsilon: 0.1\n",
      "1822  Episode Reward:  28.280222427446745 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1823  Episode Reward:  24.078537658568536 .Epsilon: 0.1\n",
      "1824  Episode Reward:  265.59739038277166 .Epsilon: 0.1\n",
      "1825  Episode Reward:  252.77081561356744 .Epsilon: 0.1\n",
      "1826  Episode Reward:  -141.08142307305877 .Epsilon: 0.1\n",
      "1827  Episode Reward:  271.8255710927227 .Epsilon: 0.1\n",
      "1828  Episode Reward:  215.01559347121292 .Epsilon: 0.1\n",
      "1829  Episode Reward:  -180.5264276920676 .Epsilon: 0.1\n",
      "1830  Episode Reward:  264.384525061688 .Epsilon: 0.1\n",
      "1831  Episode Reward:  -33.73655618705938 .Epsilon: 0.1\n",
      "1832  Episode Reward:  238.37358425233387 .Epsilon: 0.1\n",
      "1833  Episode Reward:  -43.794299126668946 .Epsilon: 0.1\n",
      "1834  Episode Reward:  -56.95169400693655 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1835  Episode Reward:  265.68059290020517 .Epsilon: 0.1\n",
      "1836  Episode Reward:  161.0171167157133 .Epsilon: 0.1\n",
      "1837  Episode Reward:  -78.66177247675371 .Epsilon: 0.1\n",
      "1838  Episode Reward:  -21.725980648745505 .Epsilon: 0.1\n",
      "1839  Episode Reward:  219.69977389324572 .Epsilon: 0.1\n",
      "1840  Episode Reward:  -181.9624182910327 .Epsilon: 0.1\n",
      "1841  Episode Reward:  -304.67464408557464 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1842  Episode Reward:  -22.12532099215838 .Epsilon: 0.1\n",
      "1843  Episode Reward:  263.0603295535823 .Epsilon: 0.1\n",
      "1844  Episode Reward:  0.8869800882022076 .Epsilon: 0.1\n",
      "1845  Episode Reward:  193.8234827826265 .Epsilon: 0.1\n",
      "1846  Episode Reward:  307.0074331046356 .Epsilon: 0.1\n",
      "1847  Episode Reward:  263.0051474086139 .Epsilon: 0.1\n",
      "1848  Episode Reward:  -228.94324960358358 .Epsilon: 0.1\n",
      "1849  Episode Reward:  -92.66587783383501 .Epsilon: 0.1\n",
      "1850  Episode Reward:  29.405773713260714 .Epsilon: 0.1\n",
      "1851  Episode Reward:  17.16579927400346 .Epsilon: 0.1\n",
      "1852  Episode Reward:  6.497391028037072 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1853  Episode Reward:  273.62111311385786 .Epsilon: 0.1\n",
      "1854  Episode Reward:  261.52455842452275 .Epsilon: 0.1\n",
      "1855  Episode Reward:  83.88368445112685 .Epsilon: 0.1\n",
      "1856  Episode Reward:  34.24347628895228 .Epsilon: 0.1\n",
      "1857  Episode Reward:  271.9927262844681 .Epsilon: 0.1\n",
      "1858  Episode Reward:  137.7694108257196 .Epsilon: 0.1\n",
      "1859  Episode Reward:  40.49840697825891 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1860  Episode Reward:  236.07215147765183 .Epsilon: 0.1\n",
      "1861  Episode Reward:  275.2286759444488 .Epsilon: 0.1\n",
      "1862  Episode Reward:  275.3366600250004 .Epsilon: 0.1\n",
      "1863  Episode Reward:  271.37936976796584 .Epsilon: 0.1\n",
      "1864  Episode Reward:  189.0402660333648 .Epsilon: 0.1\n",
      "1865  Episode Reward:  20.67488206710243 .Epsilon: 0.1\n",
      "1866  Episode Reward:  21.88028375065211 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1867  Episode Reward:  284.3850470830555 .Epsilon: 0.1\n",
      "1868  Episode Reward:  216.1611054960043 .Epsilon: 0.1\n",
      "1869  Episode Reward:  69.69362189952196 .Epsilon: 0.1\n",
      "1870  Episode Reward:  231.25270846808507 .Epsilon: 0.1\n",
      "1871  Episode Reward:  -235.65151923204004 .Epsilon: 0.1\n",
      "1872  Episode Reward:  247.3859269055824 .Epsilon: 0.1\n",
      "1873  Episode Reward:  271.7201922422156 .Epsilon: 0.1\n",
      "1874  Episode Reward:  -160.40306491658112 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1875  Episode Reward:  236.1867987970144 .Epsilon: 0.1\n",
      "1876  Episode Reward:  42.210959081545525 .Epsilon: 0.1\n",
      "1877  Episode Reward:  283.2679321894267 .Epsilon: 0.1\n",
      "1878  Episode Reward:  174.20825754025157 .Epsilon: 0.1\n",
      "1879  Episode Reward:  267.49120608756914 .Epsilon: 0.1\n",
      "1880  Episode Reward:  -33.35059102265552 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1881  Episode Reward:  -255.77936018807105 .Epsilon: 0.1\n",
      "1882  Episode Reward:  -43.88382852782297 .Epsilon: 0.1\n",
      "1883  Episode Reward:  -168.78818932356157 .Epsilon: 0.1\n",
      "1884  Episode Reward:  63.742317475388916 .Epsilon: 0.1\n",
      "1885  Episode Reward:  151.6628708357964 .Epsilon: 0.1\n",
      "1886  Episode Reward:  280.4626188415033 .Epsilon: 0.1\n",
      "1887  Episode Reward:  20.910463983320838 .Epsilon: 0.1\n",
      "1888  Episode Reward:  79.50730184640844 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1889  Episode Reward:  277.3163150786596 .Epsilon: 0.1\n",
      "1890  Episode Reward:  22.2211361854977 .Epsilon: 0.1\n",
      "1891  Episode Reward:  8.90822277796751 .Epsilon: 0.1\n",
      "1892  Episode Reward:  10.009175570433428 .Epsilon: 0.1\n",
      "1893  Episode Reward:  20.201758945093758 .Epsilon: 0.1\n",
      "1894  Episode Reward:  211.3611728781413 .Epsilon: 0.1\n",
      "1895  Episode Reward:  -245.491807728881 .Epsilon: 0.1\n",
      "1896  Episode Reward:  -115.14867919316355 .Epsilon: 0.1\n",
      "1897  Episode Reward:  -45.99130202721129 .Epsilon: 0.1\n",
      "1898  Episode Reward:  -21.17555061935066 .Epsilon: 0.1\n",
      "1899  Episode Reward:  -46.78138753306351 .Epsilon: 0.1\n",
      "1900  Episode Reward:  -312.42562562892283 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1901  Episode Reward:  -74.06100352533215 .Epsilon: 0.1\n",
      "1902  Episode Reward:  -294.02074712338845 .Epsilon: 0.1\n",
      "1903  Episode Reward:  262.16080323462063 .Epsilon: 0.1\n",
      "1904  Episode Reward:  255.23234733699837 .Epsilon: 0.1\n",
      "1905  Episode Reward:  174.2594301670457 .Epsilon: 0.1\n",
      "1906  Episode Reward:  271.71226158884537 .Epsilon: 0.1\n",
      "1907  Episode Reward:  271.5618060538503 .Epsilon: 0.1\n",
      "1908  Episode Reward:  -13.836677504178255 .Epsilon: 0.1\n",
      "1909  Episode Reward:  -14.827674606960628 .Epsilon: 0.1\n",
      "1910  Episode Reward:  -149.6382913918407 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1911  Episode Reward:  262.2425993598031 .Epsilon: 0.1\n",
      "1912  Episode Reward:  226.49230863359122 .Epsilon: 0.1\n",
      "1913  Episode Reward:  -59.11815316797975 .Epsilon: 0.1\n",
      "1914  Episode Reward:  27.325839748966317 .Epsilon: 0.1\n",
      "1915  Episode Reward:  -211.03616124710936 .Epsilon: 0.1\n",
      "1916  Episode Reward:  244.69451934060876 .Epsilon: 0.1\n",
      "1917  Episode Reward:  307.3127156503781 .Epsilon: 0.1\n",
      "1918  Episode Reward:  266.65042836031114 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1919  Episode Reward:  277.51975030721644 .Epsilon: 0.1\n",
      "1920  Episode Reward:  -197.39209660212686 .Epsilon: 0.1\n",
      "1921  Episode Reward:  252.24852799974244 .Epsilon: 0.1\n",
      "1922  Episode Reward:  -281.2308412123809 .Epsilon: 0.1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1923  Episode Reward:  208.1010838660922 .Epsilon: 0.1\n",
      "1924  Episode Reward:  281.5378230634942 .Epsilon: 0.1\n",
      "1925  Episode Reward:  272.2783647352014 .Epsilon: 0.1\n",
      "1926  Episode Reward:  23.33759787920272 .Epsilon: 0.1\n",
      "1927  Episode Reward:  253.79424546068202 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1928  Episode Reward:  249.64939138651613 .Epsilon: 0.1\n",
      "1929  Episode Reward:  223.79224972698603 .Epsilon: 0.1\n",
      "1930  Episode Reward:  -89.40948381583226 .Epsilon: 0.1\n",
      "1931  Episode Reward:  25.471751833905046 .Epsilon: 0.1\n",
      "1932  Episode Reward:  122.32425107770065 .Epsilon: 0.1\n",
      "1933  Episode Reward:  203.21688136279136 .Epsilon: 0.1\n",
      "1934  Episode Reward:  263.85371249744856 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1935  Episode Reward:  -99.86065027307967 .Epsilon: 0.1\n",
      "1936  Episode Reward:  256.41685228297956 .Epsilon: 0.1\n",
      "1937  Episode Reward:  228.53847501671245 .Epsilon: 0.1\n",
      "1938  Episode Reward:  265.92523769400304 .Epsilon: 0.1\n",
      "1939  Episode Reward:  273.73060842822326 .Epsilon: 0.1\n",
      "1940  Episode Reward:  250.5240141243601 .Epsilon: 0.1\n",
      "1941  Episode Reward:  274.67948194136886 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1942  Episode Reward:  -119.16374723447588 .Epsilon: 0.1\n",
      "1943  Episode Reward:  28.677930478608687 .Epsilon: 0.1\n",
      "1944  Episode Reward:  22.215402625425 .Epsilon: 0.1\n",
      "1945  Episode Reward:  261.6613487949152 .Epsilon: 0.1\n",
      "1946  Episode Reward:  -8.1784412985387 .Epsilon: 0.1\n",
      "1947  Episode Reward:  282.5926155114105 .Epsilon: 0.1\n",
      "1948  Episode Reward:  302.3425285936098 .Epsilon: 0.1\n",
      "1949  Episode Reward:  32.222262646431204 .Epsilon: 0.1\n",
      "1950  Episode Reward:  18.816799570309087 .Epsilon: 0.1\n",
      "1951  Episode Reward:  290.7959674181668 .Epsilon: 0.1\n",
      "1952  Episode Reward:  283.21506181105894 .Epsilon: 0.1\n",
      "1953  Episode Reward:  273.94324530853817 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1954  Episode Reward:  -156.27675824918882 .Epsilon: 0.1\n",
      "1955  Episode Reward:  273.7690316822114 .Epsilon: 0.1\n",
      "1956  Episode Reward:  28.637690245779254 .Epsilon: 0.1\n",
      "1957  Episode Reward:  -36.334835126796705 .Epsilon: 0.1\n",
      "1958  Episode Reward:  37.55201821329476 .Epsilon: 0.1\n",
      "1959  Episode Reward:  229.37200996225866 .Epsilon: 0.1\n",
      "1960  Episode Reward:  259.1423787548154 .Epsilon: 0.1\n",
      "1961  Episode Reward:  208.58580432135733 .Epsilon: 0.1\n",
      "1962  Episode Reward:  235.70584225105108 .Epsilon: 0.1\n",
      "1963  Episode Reward:  -303.1387700762314 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1964  Episode Reward:  125.3387282750999 .Epsilon: 0.1\n",
      "1965  Episode Reward:  -388.4915086874962 .Epsilon: 0.1\n",
      "1966  Episode Reward:  -9.604844826040193 .Epsilon: 0.1\n",
      "1967  Episode Reward:  25.295579678885346 .Epsilon: 0.1\n",
      "1968  Episode Reward:  278.5379052816511 .Epsilon: 0.1\n",
      "1969  Episode Reward:  12.331081828336764 .Epsilon: 0.1\n",
      "1970  Episode Reward:  -394.0811061634641 .Epsilon: 0.1\n",
      "1971  Episode Reward:  62.18841599169332 .Epsilon: 0.1\n",
      "1972  Episode Reward:  52.630739538706166 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1973  Episode Reward:  220.4259679511681 .Epsilon: 0.1\n",
      "1974  Episode Reward:  264.0123875411655 .Epsilon: 0.1\n",
      "1975  Episode Reward:  -167.430918919798 .Epsilon: 0.1\n",
      "1976  Episode Reward:  -205.17771677693418 .Epsilon: 0.1\n",
      "1977  Episode Reward:  243.14237553295914 .Epsilon: 0.1\n",
      "1978  Episode Reward:  287.5445633564141 .Epsilon: 0.1\n",
      "1979  Episode Reward:  -114.67808694604933 .Epsilon: 0.1\n",
      "1980  Episode Reward:  216.35365896973082 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1981  Episode Reward:  -13.973468937059167 .Epsilon: 0.1\n",
      "1982  Episode Reward:  270.8857088253345 .Epsilon: 0.1\n",
      "1983  Episode Reward:  -181.04211712272615 .Epsilon: 0.1\n",
      "1984  Episode Reward:  -15.478367982889353 .Epsilon: 0.1\n",
      "1985  Episode Reward:  -131.97521889637937 .Epsilon: 0.1\n",
      "1986  Episode Reward:  272.27106157247493 .Epsilon: 0.1\n",
      "1987  Episode Reward:  -48.19499297629622 .Epsilon: 0.1\n",
      "1988  Episode Reward:  2.653909258870243 .Epsilon: 0.1\n",
      "1989  Episode Reward:  33.19004674731471 .Epsilon: 0.1\n",
      "1990  Episode Reward:  -14.874084388454818 .Epsilon: 0.1\n",
      "1991  Episode Reward:  23.273920724143963 .Epsilon: 0.1\n",
      "1992  Episode Reward:  276.0478811822933 .Epsilon: 0.1\n",
      "1993  Episode Reward:  11.10268319437553 .Epsilon: 0.1\n",
      "STATIC WEIGHTS UPDATED\n",
      "1994  Episode Reward:  -126.7094110691056 .Epsilon: 0.1\n",
      "1995  Episode Reward:  256.0135508338465 .Epsilon: 0.1\n",
      "1996  Episode Reward:  30.020287820450278 .Epsilon: 0.1\n",
      "1997  Episode Reward:  -314.39152452457336 .Epsilon: 0.1\n",
      "1998  Episode Reward:  267.62066003354596 .Epsilon: 0.1\n",
      "1999  Episode Reward:  21.24540244970389 .Epsilon: 0.1\n"
     ]
    }
   ],
   "source": [
    "for episode in range ((numberEpisodes),(numberEpisodes+1500)):\n",
    "    epsilon = max (epsilon*epsilonDecay, 0.1)\n",
    "    \n",
    "    \n",
    "    done = False\n",
    "    prevObs = env.reset()\n",
    "    \n",
    "    episodeReward = 0\n",
    "    for step in range (2000):\n",
    "        if done:\n",
    "            break\n",
    "        #env.render()\n",
    "        \n",
    "\n",
    "        target = model.predict(np.expand_dims(prevObs, axis = 0))[0]\n",
    "        if (random.random()<epsilon):\n",
    "            action = random.choice([0,1,2,3 ])\n",
    "        else:\n",
    "            action = np.argmax(target)\n",
    "        \n",
    "        obs, reward, done, _ = env.step (action)\n",
    "\n",
    "\n",
    "        memoryPreviousStates[counter] = prevObs\n",
    "        memoryStates[counter] = obs\n",
    "        \n",
    "        memoryARD[counter] = [float(action), reward, float (done)]\n",
    "        \n",
    "        if (counter % 3000 == 0):\n",
    "            model.save_weights(\"lunarweights.h5\")\n",
    "            model, staticModel = updateStaticWeights(model, staticModel,tau)\n",
    "            print (\"STATIC WEIGHTS UPDATED\")\n",
    "        \n",
    "        if (itemsInMemory < (counter+1)):\n",
    "            itemsInMemory = min ((itemsInMemory+1), memorySize)\n",
    "        if (itemsInMemory >= initialiseReplayAfter):\n",
    "            executeMemoryReplayStep(memoryPreviousStates, memoryStates, memoryARD, model, staticModel, itemsInMemory)\n",
    "\n",
    "\n",
    "        prevObs = obs\n",
    "        episodeReward += reward\n",
    "        counter = (counter + 1) % memorySize\n",
    "    print (episode, \" Episode Reward: \", episodeReward, \".Epsilon:\", epsilon)\n",
    "    rewards.append(episodeReward)\n",
    "\n",
    "env.close()\n",
    "model.save_weights(\"lunarweights.h5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot (list(range(len(rewards))), rewards)\n",
    "plt.title(\"Rewards obtained along the learning process\")\n",
    "plt.xlabel(\"Episode number\")\n",
    "plt.ylabel(\"Reward obtained\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The agent has learnt to land on the moon.\n",
    "### However, it must be considered that the agent does not have any input of the surface of the moon in each episode. This results in instability given that the mountains and valleys are located in different places each time and the agent cannot know where."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0  Episode Reward:  -295.46750922065763\n",
      "1  Episode Reward:  227.57930211424892\n",
      "2  Episode Reward:  32.83854192278031\n",
      "3  Episode Reward:  247.00420060176486\n",
      "4  Episode Reward:  235.91761262820563\n",
      "5  Episode Reward:  -14.708754489741423\n",
      "6  Episode Reward:  259.0749561320472\n",
      "7  Episode Reward:  278.1739206104837\n",
      "8  Episode Reward:  -125.63615510786114\n",
      "9  Episode Reward:  27.016783195873273\n",
      "10  Episode Reward:  255.74274279375055\n",
      "11  Episode Reward:  231.45247510020738\n",
      "12  Episode Reward:  -763.6073317123885\n",
      "13  Episode Reward:  169.08154499111646\n",
      "14  Episode Reward:  158.70828490362396\n",
      "15  Episode Reward:  254.94165907190325\n",
      "16  Episode Reward:  -21.91389325278479\n",
      "17  Episode Reward:  264.6055424906254\n",
      "18  Episode Reward:  255.58705418925527\n",
      "19  Episode Reward:  22.739065478757055\n",
      "20  Episode Reward:  2.53890935058638\n",
      "21  Episode Reward:  216.23855535032604\n",
      "22  Episode Reward:  235.0771972706513\n",
      "23  Episode Reward:  -6.385638467687841\n",
      "24  Episode Reward:  18.118904573157806\n",
      "25  Episode Reward:  -85.75399869662009\n",
      "26  Episode Reward:  4.385403436155826\n",
      "27  Episode Reward:  227.7028710034279\n",
      "28  Episode Reward:  242.1981415302111\n",
      "29  Episode Reward:  -242.47349674302362\n",
      "30  Episode Reward:  -59.39239084921256\n",
      "31  Episode Reward:  30.93149800661908\n",
      "32  Episode Reward:  239.1786734306069\n",
      "33  Episode Reward:  251.5623092656186\n",
      "34  Episode Reward:  -267.6421951666993\n",
      "35  Episode Reward:  -19.232762694487676\n",
      "36  Episode Reward:  -97.36712187630572\n",
      "37  Episode Reward:  191.61148609680825\n",
      "38  Episode Reward:  -381.25934893903536\n",
      "39  Episode Reward:  215.17490640591532\n",
      "40  Episode Reward:  -105.33758558959543\n",
      "41  Episode Reward:  -317.6213751040626\n",
      "42  Episode Reward:  235.7753425211759\n",
      "43  Episode Reward:  -246.9314099043575\n",
      "44  Episode Reward:  -127.77025727142893\n",
      "45  Episode Reward:  -71.21901488304968\n",
      "46  Episode Reward:  -333.3503979718398\n",
      "47  Episode Reward:  293.6491717726843\n",
      "48  Episode Reward:  279.94547581327197\n",
      "49  Episode Reward:  201.92144555612242\n",
      "50  Episode Reward:  261.88748452384255\n",
      "51  Episode Reward:  -261.75013998315006\n",
      "52  Episode Reward:  -283.659065354187\n",
      "53  Episode Reward:  -277.0708498809587\n",
      "54  Episode Reward:  270.4037110117676\n",
      "55  Episode Reward:  -47.278606026981095\n",
      "56  Episode Reward:  -221.5076282466679\n",
      "57  Episode Reward:  -383.03532192539103\n",
      "58  Episode Reward:  -288.1433490197735\n",
      "59  Episode Reward:  -6.338364692276187\n",
      "60  Episode Reward:  230.0814000625086\n",
      "61  Episode Reward:  -17.3505523529128\n",
      "62  Episode Reward:  -20.552274655369047\n",
      "63  Episode Reward:  209.10372514639448\n",
      "64  Episode Reward:  -457.97335800106316\n",
      "65  Episode Reward:  252.0025662233531\n",
      "66  Episode Reward:  233.05414750511588\n",
      "67  Episode Reward:  -630.0598884699945\n",
      "68  Episode Reward:  -146.87117952262048\n",
      "69  Episode Reward:  -232.596384766748\n",
      "70  Episode Reward:  268.38123803093913\n",
      "71  Episode Reward:  2.494885065496419\n",
      "72  Episode Reward:  -204.04262106363944\n",
      "73  Episode Reward:  -514.7769400457119\n",
      "74  Episode Reward:  254.42343452702193\n",
      "75  Episode Reward:  172.4742508683359\n",
      "76  Episode Reward:  280.45456202234953\n",
      "77  Episode Reward:  242.10184386104171\n",
      "78  Episode Reward:  -359.81271135044534\n",
      "79  Episode Reward:  146.63133109916865\n",
      "80  Episode Reward:  -110.32715839754276\n",
      "81  Episode Reward:  -248.56446122893712\n",
      "82  Episode Reward:  -238.47327419109894\n",
      "83  Episode Reward:  233.263686886712\n",
      "84  Episode Reward:  -245.10337556961792\n",
      "85  Episode Reward:  -314.4923698405712\n",
      "86  Episode Reward:  124.27520623287452\n",
      "87  Episode Reward:  244.60839292850943\n",
      "88  Episode Reward:  226.40118835798916\n",
      "89  Episode Reward:  24.669197402543205\n",
      "90  Episode Reward:  209.9638567994973\n",
      "91  Episode Reward:  5.107636754261719\n",
      "92  Episode Reward:  -159.40163582179719\n",
      "93  Episode Reward:  -575.5946469314433\n",
      "94  Episode Reward:  -0.6495752836467972\n",
      "95  Episode Reward:  209.99661083132622\n",
      "96  Episode Reward:  12.706245561964678\n",
      "97  Episode Reward:  -170.13197756947255\n",
      "98  Episode Reward:  -209.55007126673516\n",
      "99  Episode Reward:  138.6539648641652\n"
     ]
    }
   ],
   "source": [
    "# Testing loop (Google colab cannot render the environment, only computations can be done. Render in Local Machine!)\n",
    "\n",
    "numberOfTestingEpisodes = 100\n",
    "testingRewards = []\n",
    "for episode in range (numberOfTestingEpisodes):\n",
    "    done = False\n",
    "    episodeReward = 0\n",
    "    prevObs = env.reset()\n",
    "    for step in range (1010):\n",
    "       \n",
    "        if done:\n",
    "            break\n",
    "        #env.render()\n",
    "        \n",
    "       \n",
    "\n",
    "        target = model.predict(np.expand_dims(prevObs, axis = 0))[0]\n",
    "\n",
    "        action = np.argmax(target)\n",
    "        \n",
    "        \n",
    "        obs, reward, done, info = env.step (action)\n",
    "        \n",
    "        prevObs = obs\n",
    "        episodeReward += reward\n",
    "      \n",
    "    print (episode, \" Episode Reward: \", episodeReward)\n",
    "    testingRewards.append(episodeReward)\n",
    "env.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.plot (list(range(len(testingRewards))), testingRewards)\n",
    "plt.plot (list(range(len(testingRewards))), [np.average(testingRewards)]*len(testingRewards))\n",
    "plt.title(\"Rewards obtained during Testing\")\n",
    "plt.xlabel(\"Episode number\")\n",
    "plt.ylabel(\"Reward obtained\")\n",
    "plt.legend([\"Rewards\", \"Average: %.2f\" % np.average(testingRewards)])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### After 2000 episodes the agent's performance has worsen a bit. Its results depend too much on the random surface generation in each iteration (the agent state doesn't contain information about the mountains and valleys in the environment). Furthermore, some experiences in which it would go far to the right or to the left and crash are not in its memory arrays anymore. Consequently, it has forgotten how to come back to the middle point. The version saved after 1500 episodes seems more stable:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0  Episode Reward:  281.2003966223907\n",
      "1  Episode Reward:  248.10247530273483\n",
      "2  Episode Reward:  272.5312633050604\n",
      "3  Episode Reward:  277.96126219298685\n",
      "4  Episode Reward:  270.8434278449247\n",
      "5  Episode Reward:  289.73297753724944\n",
      "6  Episode Reward:  270.0619749707963\n",
      "7  Episode Reward:  258.7046757079535\n",
      "8  Episode Reward:  239.06654695988607\n",
      "9  Episode Reward:  244.0769958934678\n",
      "10  Episode Reward:  268.04997307797987\n",
      "11  Episode Reward:  274.15303626145624\n",
      "12  Episode Reward:  257.0616837235482\n",
      "13  Episode Reward:  273.73305790190216\n",
      "14  Episode Reward:  172.33554000293952\n",
      "15  Episode Reward:  248.56759034705487\n",
      "16  Episode Reward:  214.29610403072934\n",
      "17  Episode Reward:  246.62116356530106\n",
      "18  Episode Reward:  276.8317939308931\n",
      "19  Episode Reward:  268.71008536238276\n",
      "20  Episode Reward:  270.2793117448176\n",
      "21  Episode Reward:  -207.72658107897192\n",
      "22  Episode Reward:  228.48569696048753\n",
      "23  Episode Reward:  275.470135965796\n",
      "24  Episode Reward:  266.1812901660189\n",
      "25  Episode Reward:  263.7311123347385\n",
      "26  Episode Reward:  279.40995485351\n",
      "27  Episode Reward:  265.9494590530753\n",
      "28  Episode Reward:  249.3677303993514\n",
      "29  Episode Reward:  244.6718402985045\n",
      "30  Episode Reward:  270.7371028836924\n",
      "31  Episode Reward:  245.4445330836598\n",
      "32  Episode Reward:  -240.15380768991596\n",
      "33  Episode Reward:  290.89299471085855\n",
      "34  Episode Reward:  218.2145080988015\n",
      "35  Episode Reward:  17.71026245689518\n",
      "36  Episode Reward:  278.9322487119024\n",
      "37  Episode Reward:  282.41422569143754\n",
      "38  Episode Reward:  280.4366728747125\n",
      "39  Episode Reward:  287.45953584200356\n",
      "40  Episode Reward:  28.095072531646494\n",
      "41  Episode Reward:  284.46870607769364\n",
      "42  Episode Reward:  268.7208563120359\n",
      "43  Episode Reward:  260.4264057325073\n",
      "44  Episode Reward:  274.50527353476\n",
      "45  Episode Reward:  261.24047408182537\n",
      "46  Episode Reward:  251.20892213788875\n",
      "47  Episode Reward:  276.06019852929046\n",
      "48  Episode Reward:  4.6169576518690665\n",
      "49  Episode Reward:  270.9171096336437\n",
      "50  Episode Reward:  260.6927836671641\n",
      "51  Episode Reward:  264.46428613318585\n",
      "52  Episode Reward:  235.2899908541915\n",
      "53  Episode Reward:  281.89502393970787\n",
      "54  Episode Reward:  272.4482329976578\n",
      "55  Episode Reward:  284.0943135304236\n",
      "56  Episode Reward:  229.95039644108\n",
      "57  Episode Reward:  255.94193067487424\n",
      "58  Episode Reward:  294.7720262806536\n",
      "59  Episode Reward:  276.8827034854319\n",
      "60  Episode Reward:  267.481850727947\n",
      "61  Episode Reward:  260.58577301797516\n",
      "62  Episode Reward:  285.18716591098155\n",
      "63  Episode Reward:  284.0422189996406\n",
      "64  Episode Reward:  244.70461194255876\n",
      "65  Episode Reward:  261.70558316635953\n",
      "66  Episode Reward:  240.97618017554228\n",
      "67  Episode Reward:  230.68718207382616\n",
      "68  Episode Reward:  271.7344839454428\n",
      "69  Episode Reward:  287.66245684379817\n",
      "70  Episode Reward:  280.642759963979\n",
      "71  Episode Reward:  285.88712587342695\n",
      "72  Episode Reward:  284.01205037338354\n",
      "73  Episode Reward:  233.96486189880784\n",
      "74  Episode Reward:  28.24860759383506\n",
      "75  Episode Reward:  14.317989275125242\n",
      "76  Episode Reward:  129.44900687702832\n",
      "77  Episode Reward:  300.138291573418\n",
      "78  Episode Reward:  -239.8214772222506\n",
      "79  Episode Reward:  274.5405330793228\n",
      "80  Episode Reward:  261.02555590457615\n",
      "81  Episode Reward:  -183.1771401244699\n",
      "82  Episode Reward:  241.36284636894445\n",
      "83  Episode Reward:  233.20883382314463\n",
      "84  Episode Reward:  142.86194137294032\n",
      "85  Episode Reward:  256.5195511189118\n",
      "86  Episode Reward:  288.0395429364631\n",
      "87  Episode Reward:  272.6384506992147\n",
      "88  Episode Reward:  275.8298103987729\n",
      "89  Episode Reward:  231.04951914595938\n",
      "90  Episode Reward:  244.70006342502984\n",
      "91  Episode Reward:  -5.2841246043846155\n",
      "92  Episode Reward:  276.58983249145007\n",
      "93  Episode Reward:  292.66655556295314\n",
      "94  Episode Reward:  259.2687406981042\n",
      "95  Episode Reward:  251.85711750828773\n",
      "96  Episode Reward:  279.4869061029371\n",
      "97  Episode Reward:  -97.46745243258947\n",
      "98  Episode Reward:  245.46661227580825\n",
      "99  Episode Reward:  291.8493952948463\n"
     ]
    }
   ],
   "source": [
    "# Testing loop (Google colab cannot render the environment, only computations can be done. Render in Local Machine!)\n",
    "\n",
    "model.load_weights(\"lunarLanderDiscrete1500episodes.h5\")\n",
    "numberOfTestingEpisodes = 100\n",
    "testingRewards = []\n",
    "for episode in range (numberOfTestingEpisodes):\n",
    "    done = False\n",
    "    episodeReward = 0\n",
    "    prevObs = env.reset()\n",
    "    for step in range (1010):\n",
    "       \n",
    "        if done:\n",
    "            break\n",
    "        env.render()\n",
    "        \n",
    "       \n",
    "\n",
    "        target = model.predict(np.expand_dims(prevObs, axis = 0))[0]\n",
    "\n",
    "        action = np.argmax(target)\n",
    "        \n",
    "        \n",
    "        obs, reward, done, info = env.step (action)\n",
    "        \n",
    "        prevObs = obs\n",
    "        episodeReward += reward\n",
    "      \n",
    "    print (episode, \" Episode Reward: \", episodeReward)\n",
    "    testingRewards.append(episodeReward)\n",
    "env.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot (list(range(len(testingRewards))), testingRewards)\n",
    "plt.plot (list(range(len(testingRewards))), [np.average(testingRewards)]*len(testingRewards))\n",
    "plt.title(\"Rewards obtained during Testing\")\n",
    "plt.xlabel(\"Episode number\")\n",
    "plt.ylabel(\"Reward obtained\")\n",
    "plt.legend([\"Rewards\", \"Average: %.2f\" % np.average(testingRewards)])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### This version manages to solve the environment! \n",
    "#### More than 200.0 average over 100 consecutive episodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}