easyAI 0.0.0.2

Installation

if you have pip installed, type this in a terminal

sudo pip install easyAI

Otherwise, dowload the source code (for instance on Github), unzip everything into one folder and in this folder, in a terminal, type

sudo python setup.py install

Additionnally you will need to install Numpy to be able to run some of the examples.

A quick example

Let us define the rules of a game and start a match against the AI:

from easyAI import TwoPlayersGame, Human_Player, AI_Player, Negamax

class GameOfBones( TwoPlayersGame ):
    """ In turn, the players remove one, two or three bones from a
    pile of bones. The player who removes the last bone loses. """

    def __init__(self, players):
        self.players = players
        self.pile = 20 # start with 20 bones in the pile
        self.nplayer = 1 # player 1 starts

    def possible_moves(self,move): return ['1','2','3']
    def make_move(self,move): self.pile -= int(move) # remove bones.
    def win(self): return self.pile<=0 # opponent took the last bone ?
    def is_over(self): return self.win() # Game stops when someone wins.
    def show(self): print "%d bones left in the pile"%d
    def scoring(self): return 100 if game.win() else 0 # For the AI

# Start a match (and store the history of moves when it ends)
ai = Negamax(13) # The AI will think 13 moves in advance
game = GameOfBones( [ Human_Player(), AI_Player(ai) ] )
history = game.play()

Result:

20 bones left in the pile

Player 1 what do you play ? 3

Move #1: player 1 plays 3 :
17 bones left in the pile

Move #2: player 2 plays 1 :
16 bones left in the pile

Player 1 what do you play ?

from easyAI import id_solve
r,d,m = id_solve(GameOfBones, ai_depths=range(2,20), win_score=100)

tt = DictTT()
GameOfBones.ttentry = lambda game : game.pile # key for the table
r,d,m = solve_game(GameOfBones, range(2,20), win_score=100, tt=tt)

game = GameOfBones( [  AI_Player( tt ), Human_Player() ] )
game.play() # you will always lose this game :)

Contribute !

EasyAI is an open source software originally written by Zulko and released under the MIT licence. It is very small and could really do with some improvements, so if your are a Python/AI guru maybe you can contribute through Github . Some ideas of improvement are: AI algos for incomplete information games, better game solving strategies, (efficient) use of databases to store moves, AI algorithms using parallelisation.

For troubleshooting and bug reports, the best for now is to ask on Github.