diff --git a/README.md b/README.md
index 524e06c..ef26578 100644
--- a/README.md
+++ b/README.md
@@ -1 +1,25 @@
-# sheep-flock
\ No newline at end of file
+# sheep-flock
+
+### About
+
+An agent-based model implementation for simulating a sheep flock and herd dogs. 
+
+In the .env file, you can set parameters for a simulation. We recommend focussing on these parameters:
+- N_SHEEP
+- N_DOG
+- SPAWN_CONTROLLABLE_DOG (Set to True for a controllable dog that can be controlled using the arrow keys)
+- SHEEP_SPAWN_DISTRIBUTION
+
+### Setup
+
+Use Python 3.12 or a similar version. Create a virtual environment using ``python -m venv venv``, activate it (Windows: ``venv\Scripts\activate ``, Linux/macOS: ``source venv/bin/activate``) and use ``pip install -r requirements.txt`` to install the necessary packages into the venv.
+
+To start a simulation, run the main.py.
+
+from the root directory of the project run:
+```
+python -m src.main
+```
+
+
+
diff --git a/Report.pdf b/Report.pdf
new file mode 100644
index 0000000..641fa44
Binary files /dev/null and b/Report.pdf differ
diff --git a/requirements.txt b/requirements.txt
index d120b8c..80f4f82 100644
Binary files a/requirements.txt and b/requirements.txt differ
diff --git a/src/.env b/src/.env
index 3fc247b..2cde881 100644
--- a/src/.env
+++ b/src/.env
@@ -1,8 +1,12 @@
 # Environment basics
 N_SHEEP=70
-N_DOG=4
+N_DOG=3
 SHEEP_SPAWN_DISTRIBUTION=normal  # Options: "uniform" or "normal"
 
+# Controllable dog
+SPAWN_CONTROLLABLE_DOG=False
+CONTROLLABLE_DOG_MAX_SPEED = 0.02
+
 # Sheep parameters
 ANIMAL_OBSERVATION_RADIUS=0.55
 SHEEP_MAX_SPEED=0.001
@@ -33,8 +37,3 @@ COLOR_SHEEP_DEFAULT=255,255,255
 COLOR_SHEEP_EXCITED=0,0,0
 COLOR_DOG=153,102,51
 COLOR_CONTROLLABLE_DOG=0,0,255
-
-
-# Controllable DOG
-SPAWN_CONTROLLABLE_DOG=True
-CONTROLLABLE_DOG_MAX_SPEED = 0.02
\ No newline at end of file
diff --git a/src/animals/sheep.py b/src/animals/sheep.py
index f2970a8..7c9af66 100644
--- a/src/animals/sheep.py
+++ b/src/animals/sheep.py
@@ -1,7 +1,7 @@
 import os
 from pygame import Color, Vector2
-from src.animals.animals import Animal
 from src.utils import timed
+from src.animals.animals import Animal
 import random as rand
 
 
@@ -164,6 +164,10 @@ def _calculate_separation_velocity(self, sheep):
 
     @timed
     def _calculate_dog_avoidance(self, dogs):
+
+        if not dogs:
+            return Vector2(0, 0)  # No dogs at all
+
         close_dogs = [
             dog for dog in dogs
             if (self.position - dog.position).magnitude() <= self.dog_avoidance_radius
diff --git a/src/environment.py b/src/environment.py
index 7cb526e..63c014d 100644
--- a/src/environment.py
+++ b/src/environment.py
@@ -1,12 +1,10 @@
-from distutils.util import strtobool
-
 import numpy as np
 import pygame
 import os
 from pygame import Vector2, DOUBLEBUF
-from animals.sheep import Sheep
-from animals.dog import Dog, ControllableDog
-from utils import timed
+from src.animals.sheep import Sheep
+from src.animals.dog import Dog, ControllableDog
+from src.utils import timed, strtobool
 import random as rand
 
 
@@ -60,11 +58,12 @@ def _translate_to_canvas(self, vector: Vector2):
         return translated
 
     def _init_herd(self) -> list[Sheep]:
+
         sheep = []
 
         spawn_distribution = os.getenv("SHEEP_SPAWN_DISTRIBUTION")
 
-        print(spawn_distribution)
+        print(f"spawning sheep with distribution: {spawn_distribution}")
 
         mean = [0, 0]
         cov = np.array([[0.1, 0],  # Variance for x and y (diagonal values)
@@ -119,7 +118,7 @@ def update_animals(self):
         herd_copy = self.herd.copy()
         dogs_copy = self.dogs.copy()
 
-        p_excited = 0.002
+        p_excited = 0.001
         self._choose_sheep_to_excite(p_excited)
 
         for sheep in self.herd:
diff --git a/src/main.py b/src/main.py
index 97fa9a3..58243d9 100644
--- a/src/main.py
+++ b/src/main.py
@@ -3,9 +3,14 @@
 from dotenv import load_dotenv
 load_dotenv()
 
-from environment import Environment
+from src.environment import Environment
 import os
+import random as rand
+import numpy as np
 
+seed = 2
+rand.seed(seed)
+np.random.seed(seed)
 
 if __name__ == "__main__":
     n_sheep = int(os.getenv("N_SHEEP", 0))
diff --git a/src/utils.py b/src/utils.py
index 9dc2519..c8702bd 100644
--- a/src/utils.py
+++ b/src/utils.py
@@ -4,6 +4,7 @@
 
 SHOULD_TIME = bool(os.getenv("TIME_EXECUTION", 0))
 
+
 def timed(func):
     def timer_wrapper(*args, **kwargs):
         start = time.time()
@@ -11,8 +12,19 @@ def timer_wrapper(*args, **kwargs):
         duration = time.time() - start
         open(LOG_OUTPUTFILE, "a").write(f"{func.__name__},{duration}\n")
         return res
+
     def default(*args, **kwargs):
         return func(*args, **kwargs)
-    
 
     return timer_wrapper if SHOULD_TIME else default
+
+
+def strtobool(val: str) -> int:
+    val = val.lower()
+    if val in ("y", "yes", "t", "true", "on", "1"):
+        return 1
+    elif val in ("n", "no", "f", "false", "off", "0"):
+        return 0
+    else:
+        raise ValueError(f"Invalid truth value: {val}")
+