Q_learning.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Q learning.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "q8_mfTU3AgXb"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import itertools\n",
        "import random\n",
        "import pickle"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bW30WuV1AnfH",
        "outputId": "ff9d8cee-223a-4d45-df8c-e4f4585d6f1b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "with open('/content/drive/MyDrive/RL/new/states.data', 'rb') as filehandle:\n",
        "    # read the data as binary data stream\n",
        "    STATES = pickle.load(filehandle)"
      ],
      "metadata": {
        "id": "4E3NOV3TA1nT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "with open('/content/drive/MyDrive/RL/new/transition_prob.data', 'rb') as filehandle:\n",
        "    # read the data as binary data stream\n",
        "    transition_probability = pickle.load(filehandle)"
      ],
      "metadata": {
        "id": "lHk7b1nZA-Fn"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "with open('/content/drive/MyDrive/RL/new/rewards.data', 'rb') as filehandle:\n",
        "    # read the data as binary data stream\n",
        "    REWARDS = pickle.load(filehandle)"
      ],
      "metadata": {
        "id": "LkJAUDgPJLH8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "STATES_SPACE_SIZE = len(STATES)\n",
        "ACTION_SPACE_SIZE = 9"
      ],
      "metadata": {
        "id": "wnb9_9GzBAFY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "STATES = np.asarray(STATES) "
      ],
      "metadata": {
        "id": "OgbC6YWTBEW2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Q = np.ones((STATES_SPACE_SIZE, ACTION_SPACE_SIZE))"
      ],
      "metadata": {
        "id": "CzeqjAT1BKC_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Q learning"
      ],
      "metadata": {
        "id": "-tchgoH8hzhW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def check_game_over_3(markers):\n",
        "  game_over = False\n",
        "  tie = False\n",
        "  winner =0\n",
        "  x_pos = 0\n",
        "  for x in markers:\n",
        "    #check columns\n",
        "    if sum(x) == 3:\n",
        "      winner = 1\n",
        "      game_over = True\n",
        "    if sum(x) == -3:\n",
        "      winner = 2\n",
        "      game_over = True\n",
        "    \n",
        "    #check rows\n",
        "    if markers[0][x_pos] + markers [1][x_pos] + markers [2][x_pos] == 3:\n",
        "      winner = 1\n",
        "      game_over = True\n",
        "    if markers[0][x_pos] + markers [1][x_pos] + markers [2][x_pos] == -3:\n",
        "      winner = 2\n",
        "      game_over = True\n",
        "    x_pos += 1\n",
        "\n",
        "  #check cross\n",
        "  if markers[0][0] + markers[1][1] + markers [2][2] == 3 or markers[2][0] + markers[1][1] + markers [0][2] == 3:\n",
        "    winner = 1\n",
        "    game_over = True\n",
        "  if markers[0][0] + markers[1][1] + markers [2][2] == -3 or markers[2][0] + markers[1][1] + markers [0][2] == -3:\n",
        "    winner = 2\n",
        "    game_over = True\n",
        "\n",
        "  #check for tie\n",
        "  if game_over == False:\n",
        "    tie = True\n",
        "    for row in markers:\n",
        "      for i in row:\n",
        "        if i == 0:\n",
        "          tie = False\n",
        "    #if it is a tie, then call game over and set winner to 0 (no one)\n",
        "    if tie == True:\n",
        "      game_over = True\n",
        "      winner = 0\n",
        "  return game_over,winner,tie\n",
        "  # if game_over == False:"
      ],
      "metadata": {
        "id": "hhfhQ_qP9M2D"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "beta = 0.2\n",
        "gamma = 0.1\n",
        "s_i = STATES[0].copy()\n",
        "wd = 0\n",
        "while True:\n",
        "  Q_temp = Q.copy()\n",
        "  a = np.where(s_i==0)[0]\n",
        "  if len(a) == 0:\n",
        "    a = range(9)\n",
        "  a = random.choice(a)\n",
        "  ind = np.where((STATES==s_i).all(-1))[0][0] # index of current state\n",
        "  ind2 = np.random.choice(np.arange(STATES_SPACE_SIZE),1,p= transition_probability[ind][a])[0]\n",
        "  R = REWARDS[ind2]\n",
        "  maxb = np.max(Q[ind2])\n",
        "  Q[ind][a] += beta*(R + gamma*(maxb) - Q[ind,a])\n",
        "  s_i = STATES[ind2].copy()\n",
        "  print(np.max(np.absolute(Q_temp - Q) ) )\n",
        "  if np.max(np.absolute(Q_temp - Q))<0.0001:\n",
        "    wd+=1\n",
        "  else:\n",
        "    wd = 0\n",
        "  if wd == 10:\n",
        "    break\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S6frHdOvh1aW",
        "outputId": "c0d7ecd1-c6bf-4c9e-d8d4-5daf1db192cb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "0.8396853428739437\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pi_star = [0]*len(STATES)\n",
        "for i in range(3381):\n",
        "  \n",
        "  pi_star[i] = np.argmax(Q[i])"
      ],
      "metadata": {
        "id": "585qgL9msbcU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#import modules\n",
        "# import pygame\n",
        "# import numpy as np\n",
        "# import pickle\n",
        "import itertools\n",
        "# from pygame.locals import *\n",
        "# np.seterr(divide='ignore', invalid='ignore')\n",
        "'''\n",
        "pygame.init()\n",
        "\n",
        "screen_height = 300\n",
        "screen_width = 300\n",
        "line_width = 6\n",
        "screen = pygame.display.set_mode((screen_width, screen_height))\n",
        "pygame.display.set_caption('Tic Tac Toe')\n",
        "\n",
        "\n",
        "\n",
        "#define colours\n",
        "red = (255, 0, 0)\n",
        "green = (0, 255, 0)\n",
        "blue = (0, 0, 255)\n",
        "\n",
        "#define font\n",
        "font = pygame.font.SysFont(None, 40)\n",
        "'''\n",
        "#define variables\n",
        "clicked = False\n",
        "player = 1\n",
        "pos = (0,0)\n",
        "markers = []\n",
        "game_over = False\n",
        "winner = 0\n",
        "\n",
        "#setup a rectangle for \"Play Again\" Option\n",
        "# again_rect = Rect(screen_width // 2 - 80, screen_height // 2, 160, 50)\n",
        "\n",
        "#create empty 3 x 3 list to represent the grid\n",
        "for x in range (3):\n",
        "\trow = [0] * 3\n",
        "\tmarkers.append(row)\n",
        "\n",
        "\n",
        "'''\n",
        "def draw_board():\n",
        "\tbg = (255, 255, 210)\n",
        "\tgrid = (50, 50, 50)\n",
        "\tscreen.fill(bg)\n",
        "\tfor x in range(1,3):\n",
        "\t\tpygame.draw.line(screen, grid, (0, 100 * x), (screen_width,100 * x), line_width)\n",
        "\t\tpygame.draw.line(screen, grid, (100 * x, 0), (100 * x, screen_height), line_width)\n",
        "\n",
        "def draw_markers():\n",
        "\tx_pos = 0\n",
        "\tfor x in markers:\n",
        "\t\ty_pos = 0\n",
        "\t\tfor y in x:\n",
        "\t\t\tif y == 1:\n",
        "\t\t\t\tpygame.draw.line(screen, red, (x_pos * 100 + 15, y_pos * 100 + 15), (x_pos * 100 + 85, y_pos * 100 + 85), line_width)\n",
        "\t\t\t\tpygame.draw.line(screen, red, (x_pos * 100 + 85, y_pos * 100 + 15), (x_pos * 100 + 15, y_pos * 100 + 85), line_width)\n",
        "\t\t\tif y == -1:\n",
        "\t\t\t\tpygame.draw.circle(screen, green, (x_pos * 100 + 50, y_pos * 100 + 50), 38, line_width)\n",
        "\t\t\ty_pos += 1\n",
        "\t\tx_pos += 1\t\n",
        "\n",
        "'''\n",
        "def check_game_over(markers = markers):\n",
        "\tglobal game_over\n",
        "\tglobal winner\n",
        "\n",
        "\tx_pos = 0\n",
        "\tfor x in markers:\n",
        "\t\t#check columns\n",
        "\t\tif sum(x) == 3:\n",
        "\t\t\twinner = 1\n",
        "\t\t\tgame_over = True\n",
        "\t\tif sum(x) == -3:\n",
        "\t\t\twinner = 2\n",
        "\t\t\tgame_over = True\n",
        "\t\t\n",
        "\t\t#check rows\n",
        "\t\tif markers[0][x_pos] + markers [1][x_pos] + markers [2][x_pos] == 3:\n",
        "\t\t\twinner = 1\n",
        "\t\t\tgame_over = True\n",
        "\t\tif markers[0][x_pos] + markers [1][x_pos] + markers [2][x_pos] == -3:\n",
        "\t\t\twinner = 2\n",
        "\t\t\tgame_over = True\n",
        "\t\tx_pos += 1\n",
        "\n",
        "\t#check cross\n",
        "\tif markers[0][0] + markers[1][1] + markers [2][2] == 3 or markers[2][0] + markers[1][1] + markers [0][2] == 3:\n",
        "\t\twinner = 1\n",
        "\t\tgame_over = True\n",
        "\tif markers[0][0] + markers[1][1] + markers [2][2] == -3 or markers[2][0] + markers[1][1] + markers [0][2] == -3:\n",
        "\t\twinner = 2\n",
        "\t\tgame_over = True\n",
        "\n",
        "\t#check for tie\n",
        "\tif game_over == False:\n",
        "\t\ttie = True\n",
        "\t\tfor row in markers:\n",
        "\t\t\tfor i in row:\n",
        "\t\t\t\tif i == 0:\n",
        "\t\t\t\t\ttie = False\n",
        "\t\t#if it is a tie, then call game over and set winner to 0 (no one)\n",
        "\t\tif tie == True:\n",
        "\t\t\tgame_over = True\n",
        "\t\t\twinner = 0\n",
        "\n",
        "\n",
        "'''\n",
        "def draw_game_over(winner):\n",
        "\n",
        "\tif winner != 0:\n",
        "\t\tend_text = \"Player \" + str(winner) + \" wins!\"\n",
        "\telif winner == 0:\n",
        "\t\tend_text = \"You have tied!\"\n",
        "\n",
        "\tend_img = font.render(end_text, True, blue)\n",
        "\tpygame.draw.rect(screen, green, (screen_width // 2 - 100, screen_height // 2 - 60, 200, 50))\n",
        "\tscreen.blit(end_img, (screen_width // 2 - 100, screen_height // 2 - 50))\n",
        "\n",
        "\tagain_text = 'Play Again?'\n",
        "\tagain_img = font.render(again_text, True, blue)\n",
        "\tpygame.draw.rect(screen, green, again_rect)\n",
        "\tscreen.blit(again_img, (screen_width // 2 - 80, screen_height // 2 + 10))\n",
        "\n",
        "'''\n",
        "def check_game_over_2(x):\n",
        "\t\ty = x.copy()\n",
        "\t\ty = np.array(y).reshape(3,3)\n",
        "\t\ty[np.where(y==2)] = -1\n",
        "\t\t# check for game over\n",
        "\t\tgame_over = False\n",
        "\t\tcheck_game_over(y)\n",
        "\n",
        "''' Defining STATE SPACE and required parameters'''\n",
        "'''\n",
        "states_0 = [[0]*9]\n",
        "\n",
        "states_1 = []\n",
        "board_pos = [i for i in range(9)]\n",
        "for i in board_pos:\n",
        "  for j in board_pos:\n",
        "    if i!=j:\n",
        "      x = [0]*9\n",
        "      x[i] = 1\n",
        "      x[j] = 2\n",
        "      states_1.append(x)\n",
        "\n",
        "# states_2\n",
        "states_2 = []\n",
        "for s in states_1:\n",
        "  indices = [i for i, x in enumerate(s) if x == 1 or x == 2]\n",
        "  board_pos = [i for i in range(9)]\n",
        "  board_pos = list(set(board_pos) - set(indices))\n",
        "  for i in board_pos:\n",
        "    for j in board_pos:\n",
        "      if i!=j:\n",
        "        x = s.copy()\n",
        "        x[i] = 1\n",
        "        x[j] = 2\n",
        "        if x not in states_2:\n",
        "          states_2.append(x)\n",
        "\n",
        "# states_3\n",
        "TERMINAL_STATES = []\n",
        "states_3 = []\n",
        "for s in states_2:\n",
        "  indices = [i for i, x in enumerate(s) if x == 1 or x == 2]\n",
        "  board_pos = [i for i in range(9)]\n",
        "  board_pos = list(set(board_pos) - set(indices))\n",
        "  # print(len(board_pos))\n",
        "  for i in board_pos:\n",
        "    for j in board_pos:\n",
        "      if i!=j:\n",
        "        x = s.copy()\n",
        "        # print(x,i,j)\n",
        "        x[i] = 1\n",
        "        # y = x.copy()\n",
        "        # y = np.array(y).reshape(3,3)\n",
        "        # y[np.where(y==2)] = -1\n",
        "        # # check for game over\n",
        "        game_over = False\n",
        "        check_game_over_2(x)\n",
        "        # if game is over then state_3.append(x) else\n",
        "        if(game_over == True):\n",
        "          # print(\"matrix\\n\",y)\n",
        "          if x not in TERMINAL_STATES:\n",
        "            TERMINAL_STATES.append(x)\n",
        "            break\n",
        "        else:\n",
        "          x[j] = 2\n",
        "          if x not in states_3:\n",
        "            states_3.append(x)\n",
        "\n",
        "# states_4\n",
        "states_4 = []\n",
        "# check for the\n",
        "for s in states_3:\n",
        "  indices = [i for i, x in enumerate(s) if x == 1 or x == 2]\n",
        "  board_pos = [i for i in range(9)]\n",
        "  board_pos = list(set(board_pos) - set(indices))\n",
        "  for i in board_pos:\n",
        "    for j in board_pos:\n",
        "      if i!=j:\n",
        "        x = s.copy()\n",
        "        x[i] = 1\n",
        "        x[j] = 2\n",
        "        if x not in states_4:\n",
        "          states_4.append(x)\n",
        "'''\n",
        "'''\n",
        "with open('states.data', 'rb') as filehandle:\n",
        "    # read the data as binary data stream\n",
        "    STATES = pickle.load(filehandle)\n",
        "\n",
        "# STATES = states_0+states_1+states_2+states_3+states_4+TERMINAL_STATES\n",
        "ACTION_SPACE = [i for i in range(9)]\n",
        "\n",
        "STATE_SPACE_SIZE = len(STATES)\n",
        "ACTION_SPACE_SIZE = len(ACTION_SPACE)\n",
        "\n",
        "'''\n",
        "\n",
        "'''\n",
        "transition_probability = np.array([[[0.0]*STATE_SPACE_SIZE]*ACTION_SPACE_SIZE]*STATE_SPACE_SIZE)\n",
        "\n",
        "\n",
        "def generate_transition_prob():\n",
        "  for i in range(STATE_SPACE_SIZE):\n",
        "  \tif STATES[i] in TERMINAL_STATES:\n",
        "  \t\tcontinue\n",
        "  \tfor j in range(ACTION_SPACE_SIZE):\n",
        "  \t\tfor k in range(STATE_SPACE_SIZE):\n",
        "  \t\t\tbd = STATES[i]\n",
        "  \t\t\tbd_2 = STATES[k]\n",
        "  \t\t\tif(bd[j] == 0 and bd_2[j]==1):\n",
        "  \t\t\t\ta = bd.copy()\n",
        "  \t\t\t\ta[j] = 1\n",
        "  \t\t\t\tgame_over=False\n",
        "  \t\t\t\tcheck_game_over_2(a)\n",
        "  \t\t\t\tif game_over==True:\n",
        "  \t\t\t\t\tt_index = np.where((STATES==a).all(-1))[0][0]\n",
        "  \t\t\t\t\ttransition_probability[i][j][t_index]=1.0\n",
        "  \t\t\t\telse:\n",
        "  \t\t\t\t\tcheck = np.subtract(bd_2,a)\n",
        "  \t\t\t\t\tif(np.sum(check)==2 and np.min(check)==0 and np.max(check)==2):\n",
        "  \t\t\t\t\t\ttransition_probability[i][j][k] = np.random.randint(1,100,size=1)[0]\n",
        "\n",
        "\n",
        "generate_transition_prob()\n",
        "\n",
        "for i in range(STATE_SPACE_SIZE):\n",
        "  for j in range(ACTION_SPACE_SIZE):\n",
        "  \tprob_sum = np.sum(transition_probability[i][j])\n",
        "  \tif prob_sum>0:\n",
        "\t    transition_probability[i][j] = transition_probability[i][j]/prob_sum\n",
        "\t    # print(\"sum=\",np.sum(transition_probability[i][j]))\n",
        "# print(transition_probability[0][2])\n",
        "\n",
        "'''\n",
        "'''\n",
        "STATES = np.asarray(STATES) \n",
        "with open('transition_prob.data', 'rb') as filehandle:\n",
        "    # read the data as binary data stream\n",
        "    transition_probability = pickle.load(filehandle)\n",
        "##################################################\n",
        "\n",
        "with open('p_policy_iteration.data', 'rb') as filehandle:\n",
        "    # read the data as binary data stream\n",
        "    pi_star = pickle.load(filehandle)\n",
        "'''\n",
        "#main loop\n",
        "win_count,tie_count,loss_count = 0,0,0\n",
        "run = True\n",
        "current_state = STATES[0]\n",
        "ind = 0\n",
        "while run:\n",
        "\t#draw board and markers first\n",
        "\t'''\n",
        "\tdraw_board()\n",
        "\tdraw_markers()\n",
        "\t\n",
        "\t#handle events\n",
        "\tfor event in pygame.event.get():\n",
        "\t\t# print(markers)\n",
        "\t\t#handle game exit\n",
        "\t\tif event.type == pygame.QUIT:\n",
        "\t\t\trun = False\n",
        "\t\t'''\n",
        "\t\t#run new game\n",
        "\tif game_over == False:\n",
        "\t\t#check for mouseclick\n",
        "\n",
        "\t\t# if event.type == pygame.MOUSEBUTTONDOWN and clicked == False:\n",
        "\t\t\t# clicked = True\n",
        "\t\t# if event.type == pygame.MOUSEBUTTONUP and clicked == True:\n",
        "\t\t# clicked = False\n",
        "\t\t# pos = pygame.mouse.get_pos()\n",
        "\t\t# cell_x = pos[0] // 100 # cell_x = pos[0]\n",
        "\t\t# cell_y = pos[1] // 100 # cell_y = pos[1]\n",
        "\t\t# print(\"cell_x=\",cell_x)\n",
        "\t\t# print(\"cell_y=\",cell_y)\n",
        "\t\t# y = np.array(markers.copy())\n",
        "\t\t# y = y.reshape(1,-1)\n",
        "\t\t# y[np.where(y==-1)] = 2\n",
        "\t\t# y = y.tolist()[0]\n",
        "\n",
        "\t\tactionn = pi_star[ind]\n",
        "\t\tif markers[actionn//3][actionn%3] == 0:\n",
        "\t\t\tmarkers[actionn//3][actionn%3] = 1\n",
        "\t\t\tprint(\"actionn\",actionn)\n",
        "\t\t\tgame_over=False\n",
        "\t\t\tcheck_game_over(markers)\n",
        "\t\t\t\t# draw_markers()\n",
        "\t\t\tif game_over == False:\n",
        "\n",
        "\t\t\t\tprint(\"markers_1=\",markers)\n",
        "\n",
        "\t\t\t\tprint(\"ind=\",ind)\t\n",
        "\t\t\t\ty = np.random.choice(np.arange(STATES_SPACE_SIZE),1,p= transition_probability[ind][actionn])[0]\n",
        "\t\t\t\t\n",
        "\t\t\t\tprint(\"index=\",y)\n",
        "\t\t\t\tnext_state = STATES[y].copy()\n",
        "\t\t\t\tcurrent_state = next_state.copy()\n",
        "\t\t\t\tprint(\"current_state = \", current_state)\n",
        "\t\t\t\tnext_state[np.where(next_state==2)] = -1\n",
        "\t\t\t\tmarkers = next_state.reshape(3,3).tolist()\n",
        "\t\t\t\tprint(\"markers_2-\",markers)\n",
        "\t\t\t\tind = np.where((STATES==current_state).all(-1))[0][0]\n",
        "\t\t\t\t# draw_markers()\n",
        "\t\t\t\t# player *= -1\n",
        "\t\t\t\n",
        "\t\t\t\tcheck_game_over(markers)\n",
        "\n",
        "\t#check if game has been won\n",
        "\tif game_over == True:\n",
        "\t\tif winner == 1:\n",
        "\t\t\twin_count+=1\n",
        "\t\telif winner == 2:\n",
        "\t\t\tloss_count+=1\n",
        "\t\telse:\n",
        "\t\t\ttie_count+=1\n",
        "\t\tif win_count+loss_count+tie_count == 1000:\n",
        "\t\t\tbreak\n",
        "\t\tcurrent_state = STATES[0]\n",
        "\t\tind = 0\n",
        "\t\t'''\n",
        "\t\tdraw_game_over(winner)\n",
        "\t\t#check for mouseclick to see if we clicked on Play Again\n",
        "\t\tif event.type == pygame.MOUSEBUTTONDOWN and clicked == False:\n",
        "\t\t\tclicked = True\n",
        "\t\tif event.type == pygame.MOUSEBUTTONUP and clicked == True:\n",
        "\t\t\tclicked = False\n",
        "\t\t\tpos = pygame.mouse.get_pos()\n",
        "\t\t\tif again_rect.collidepoint(pos):\n",
        "\t\t\t\t'''\n",
        "\t\t\t\t#reset variables\n",
        "\t\tgame_over = False\n",
        "\t\tplayer = 1\n",
        "\t\tpos = (0,0)\n",
        "\t\tmarkers = []\n",
        "\t\twinner = 0\n",
        "\t\t#create empty 3 x 3 list to represent the grid\n",
        "\t\tfor x in range (3):\n",
        "\t\t\trow = [0] * 3\n",
        "\t\t\tmarkers.append(row)\n",
        "\n",
        "\t#update display\n",
        "\t# pygame.display.update()\n",
        "\n",
        "# pygame.quit()\n",
        "print(\"win count:\",win_count)\n",
        "print(\"loss_count :\",loss_count)\n",
        "print(\"tie count:\",tie_count)\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 339
        },
        "id": "P4jWjTHOyMS5",
        "outputId": "51e65a92-f26a-4a68-b91c-90e6074f0696"
      },
      "execution_count": null,
      "outputs": [
        {
          "metadata": {
            "tags": null
          },
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "actionn 0\n",
            "markers_1= [[1, 0, 0], [0, 0, 0], [0, 0, 0]]\n",
            "ind= 0\n",
            "index= 6\n",
            "current_state =  [1 0 0 0 0 0 2 0 0]\n",
            "markers_2- [[1, 0, 0], [0, 0, 0], [-1, 0, 0]]\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "KeyboardInterrupt",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-14-0d4aaba30a6a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m    309\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    310\u001b[0m                 \u001b[0mactionn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpi_star\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mind\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 311\u001b[0;31m                 \u001b[0;32mif\u001b[0m \u001b[0mmarkers\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mactionn\u001b[0m\u001b[0;34m//\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mactionn\u001b[0m\u001b[0;34m%\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    312\u001b[0m                         \u001b[0mmarkers\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mactionn\u001b[0m\u001b[0;34m//\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mactionn\u001b[0m\u001b[0;34m%\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    313\u001b[0m                         \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"actionn\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mactionn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "random.choice([])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 287
        },
        "id": "fZwC8GRfsD8c",
        "outputId": "f30db35e-20c0-4335-c0c6-d5ed5ed4f609"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "IndexError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-17-1767171d5177>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mrandom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mchoice\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/lib/python3.7/random.py\u001b[0m in \u001b[0;36mchoice\u001b[0;34m(self, seq)\u001b[0m\n\u001b[1;32m    259\u001b[0m             \u001b[0mi\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_randbelow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mseq\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    260\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 261\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mIndexError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Cannot choose from an empty sequence'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    262\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mseq\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    263\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mIndexError\u001b[0m: Cannot choose from an empty sequence"
          ]
        }
      ]
    }
  ]
}