This is our Project for the CentraleSupelec's Reinforcement Learning course, a Pac-Man. The purpose of this work was to train in the best way possible different agents (Q- Learning, Expected-Sarsa, Deep Q-Learning) in a Reinforcement Learning environ- ment of the Game Pac-Man.
- Chloé Daems
- Anne-Claire Laisney
- Amir Mahmoudi
Python 3.9
- matplotlib
- numpy
- turtle
You can see our pipeline in the .ipynb file with the trainings and results of the Q learning and expected Sarsa Agents; If you want to try our DQN.py, you can run the following command on the terminal :
$ python DQN.py
Here you can find examples of the turtle render for the small and medium grids for the trained Sarsa Agent.
You can find the details of agents implementations in our report: 'PacMan_Report.pdf'.