Pac-Man

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.

Authors 🧠

• Chloé Daems
• Anne-Claire Laisney
• Amir Mahmoudi

Requirements 💻

Python 3.9

• matplotlib
• numpy
• turtle

Getting Started 🐣

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

Some Results 💰

Here you can find examples of the turtle render for the small and medium grids for the trained Sarsa Agent.

Implementation ✍️

You can find the details of agents implementations in our report: 'PacMan_Report.pdf'.