Download project. Navigate to directory. Do python game.py, and type in arthur when prompted for agent module.
(Note: to adjust how long the computer player "thinks" about its next move, you can vary the default depth parameter of the look ahead search. Go into arthur.py and change depth=x parameter of the function move_function.)
checkers.py
This file contains the definition of the CheckerBoard class. Its methods include new game
initialization, ASCII printed output, and getting legal moves from a given state.
agent.py
This file contains the implementation of the AI CheckersAgent class. All that is required
of a CheckersAgent is that it have a function move_function() that takes in a game state and
returns a legal move.
arthur.py
This file contains the implementation of an agent that is inspired by Arthur Samuel's
historic machine learning checkers program.
game.py
This file contains the harness for running an actual game of checkers.
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