In this project, you'll be implementing the Expectimax algorithm and a better evaluation function for the Pac-Man game.
This project requires Python version 3.6 or higher.
The following libraries are required to run the project:
- os
- time
- random
- numpy
- tkinter
To run the code, use the following command:
python3 pacman.py -l smallClassic -p ExpectimaxAgent -a evalFn=better -a depth=3 -q -n 20
This command will run the Pac-Man game using the ExpectimaxAgent class with the better evaluation function and a search depth of 3. The game will be played in quiet mode (i.e., without displaying graphics) and 20 games will be played.
**The available command line arguments are: **
- -l: Specifies the layout to use for the game. The available options are smallClassic and mediumClassic. If not specified, the mediumClassic layout is used by default.
- -p: Specifies the agent to use for the game.
- -a: Specifies additional arguments for the agent. You can specify the evaluation function using evalFn=better or the search depth using depth=3.
- -n: Specifies the number of games to play.
- -q: Makes the game run in quiet mode, without displaying graphics.