def default(self, c):
# c is the chosen move, else an error
# c should be in the range A-F
c = c.upper()
opts = ['A', 'B', 'C', 'D', 'E', 'F']
try:
move = s.translateMove(self.game.gamestate, opts.index(c))
self.game.priorstate = self.game.gamestate[:]
self.game.gamestate = s.doMove(self.game.gamestate, move)
if s.isGameOver(self.game.gamestate):
raise EndGame(self.game.gamestate)
except s.InvalidMove:
print("That is not a legal move.")
return
except s.InvalidPlayer:
print("You're not valid.")
return
except s.InvalidIndex as e:
print("That index is invalid.")
raise e
return
except ValueError:
print("You must choose one of the six bowls for your move "
"(letters A-F).")
return
except Exception as e:
raise e
return
self.game.betweenMoves()
self.setPrompt()
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 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)
def betweenMoves(self):
current = s.getCurrentPlayer(self.gamestate)
module = self.player_algorithm.get(current)
isHumanNext = True if module is None else False
while not isHumanNext:
if s.isGameOver(self.gamestate):
raise EndGame(self.gamestate)
current = s.getCurrentPlayer(self.gamestate)
module = self.player_algorithm.get(current)
isHumanNext = True if module is None else False
if not isHumanNext:
try:
d.drawState(self.gamestate, self.priorstate)
cprint("My move!", PLAYER_COLORS[current])
move = module.move(self.gamestate)
self.priorstate = self.gamestate[:]
self.gamestate = s.doMove(self.gamestate, move)
cprint(module.taunt(), PLAYER_COLORS[current])
except s.NoMoves as n:
cprint("Oops! I have no moves!", PLAYER_COLORS[current])
raise EndGame(self.gamestate)
except Exception:
raise NoAI(current)
pass