Skip to content

README.md

Latest commit

 

History

History
23 lines (17 loc) · 901 Bytes

README.md

File metadata and controls

23 lines (17 loc) · 901 Bytes

Snake Reinforcement Learning

Code for training a Deep Reinforcement Learning agent to play the game of Snake. The agent takes 2 frames of the game as input (image) and predicts the action values for the next action to take.

Running Graded Assignment 02

Run training.py to train the model. Run game_visualization.py to generate .mp4 files with examples of models playing the game. (fill the "iterations" list with the iteration numbers of the models you want to test)

Additional Dependencies

The game_visualization.py requires you to use ffmpeg https://www.gyan.dev/ffmpeg/builds/

  • Download "ffmpeg-2024-11-25-git-04ce01df0b-full_build.7z"
  • Extract the file
  • Add the path to the extracted folder's /bin to system PATH
  • Restart terminal or do $env:Path += PATH_TO_BIN

If there is any confusion regarding the code, look for docstrings and comments. It should be thoroughly documented.