AI-Snake

Reinforcement Learning Snake Game

Pre-Requirements:

• python3
• Google Chrome

Install Python Dependencies

pip3 install -r requirements.txt

Setup on Windows System:

• Download suitable chrome driver from: https://chromedriver.chromium.org/downloads
• Extract the .zip file. Copy the chromedriver.exe in the cloned directory folder (AI-snake/chromedriver.exe)
• Install Pillow(PIL):

  pip3 install Pillow==2.2.1

• Open Deep_Reinforcement_Learning_Snake.py, Comment out line 9 and 101 and un-comment line 8 and 100

Setup on Linux System:

• Install chrome driver:

  sudo apt-get install chromium-chromedriver

• Install Pyscreenshot:

  sudo pip3 install pyscreenshot

• Open Deep_Reinforcement_Learning_Snake.py, Comment out line 8 and 100 and un-comment line 9 and 101

CNN Network Architecture

Configuration:

• You can open Deep_Reinforcement_Learning_Snake.py and change the following parameters:

  img_rows, img_cols = 64,64
  SPEED = 360
  WIDTH = 8
  HEIGHT = 8
  ACTIONS = 4 
  GAMMA = 0.99 
  OBSERVATION = 65.
  EXPLORE = 70
  FINAL_EPSILON = 0.1
  INITIAL_EPSILON = 1
  REPLAY_MEMORY = 50000
  BATCH = 64
  FRAME_PER_ACTION = 1
  LEARNING_RATE = 1e-4
  img_channels = 4
  

Start Training:

python3 Deep_Reinforcement_Learning_Snake.py

Checking the scores:

• File data/scores_df.csv contains scores of each game played by our model.
• File data/actions_df.csv contains action at each step taken by the model.
• File data/loss_df.csv contains loss at each step taken by the model.
• File data/time_df.csv contains seconds played of each game.

Reference:

https://github.com/yenchenlin/DeepLearningFlappyBird

https://medium.com/acing-ai/how-i-build-an-ai-to-play-dino-run-e37f37bdf153