Python pacman is a traditional pacman game, auto completed by search and agent algorithms. Each of the following sub heading is a seperate artifical intelligence challenge.
If you wish to manually start playing the game, start pacman.py:
python pacman.py
The Pac-Man projects are written in Python 2.7 and do not depend on any packages external to a standard Python distribution.
Search implements depth-first, breadth-first, uniform cost, and A* search algorithms. These algorithms are used to solve navigation and traveling salesman problems in the Pacman world. These search alogorithms use functions from a node class, which helps store and track data.
To read the full search project details and problems, click here.
python pacman.py -l tinyMaze -p SearchAgent -a fn=tinyMazeSearch
python pacman.py -l tinyMaze -p SearchAgent
python pacman.py -l mediumMaze -p SearchAgent
python pacman.py -l bigMaze -z .5 -p SearchAgent
python pacman.py -l mediumMaze -p SearchAgent -a fn=bfs
python pacman.py -l bigMaze -p SearchAgent -a fn=bfs -z .5
python pacman.py -l mediumMaze -p SearchAgent -a fn=ucs
python pacman.py -l mediumDottedMaze -p StayEastSearchAgent
python pacman.py -l mediumScaryMaze -p StayWestSearchAgent
python pacman.py -l bigMaze -z .5 -p SearchAgent -a fn=astar,heuristic=manhattanHeuristic
Bonus problems are not yet completed.
Classic Pacman is modeled as both an adversarial and a stochastic search problem. Multi-Agent implement multiagent minimax and expectimax algorithms, as well as designing evaluation functions.
Currently being worked on.
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#Credits
The projects were developed by John DeNero, Dan Klein, Pieter Abbeel, and many others.