def play_one_game(players, lucky):
game = s.init()
done = False
moves = []
while not done:
# do move for someone
player = s.getCurrentPlayer(game)
if needRandomMove(len(moves)):
move = lucky.move(game)
else:
move = players[player]['ai'].move(game)
if move is None:
logger.error("null move! ", game)
mt = [s.flipBoardCurrentPlayer(game), s.flipMove(move, player), player]
moves.append(mt)
game = s.doMove(game, move)
done = s.isGameOver(game)
winner = s.getWinner(game)
score = s.getScore(game)
# make training set with move, gamestate, and 1 for win, 0 for lose
trainingset = [
d[0:2] + [int(winner == d[2])] + list(score)[::1 - d[2] * 2]
for d in moves
]
for move in trainingset:
results.info(move)
i = 0
for p in players:
isWinner = (1 if i == winner else 0)
p['ai'].gameOver(isWinner)
p['wins'] += isWinner
i += 1
return (winner, trainingset)
def play_game(players):
game = s.init()
done = False
moves = []
while not done:
# do move for someone
player = s.getCurrentPlayer(game)
move = players[player]['ai'].move(game)
if move is None:
print("null move! ", game)
mt = {
"move": s.flipMove(move, player),
"board": s.flipBoardCurrentPlayer(game),
"player": player,
"name": players[player]['module'].__name__
}
moves.append(mt)
game = s.doMove(game, move)
done = s.isGameOver(game)
winner = s.getWinner(game)
# make training set with move, gamestate, and 1 for win, 0 for lose
trainingset = [dict(d, winner=int(winner == d['player'])) for d in moves]
i = 0
for p in players:
p['ai'].gameOver(i == winner)
i += 1
return (winner, trainingset)
def __init__(self, opponent):
self.player_algorithm = {}
cprint("Player 1 is human.", PLAYER_COLORS[0])
for player in range(1, s.NUM_PLAYERS):
self.choosePlayer(player, opponent)
self.gamestate = s.init()
self.priorstate = self.gamestate[:]
self.betweenMoves()
def play_game(*players):
game = s.init()
done = False
while not done:
player = s.getCurrentPlayer(game)
move = players[player].move(game)
game = s.doMove(game, move)
done = s.isGameOver(game)
return s.getWinner(game)