示例#1
0
文件: pit.py 项目: kandluis/terrazero
from utils import *

"""
use this script to play any two agents against each other, or play manually with
any agent.
"""

g = OthelloGame(6)

# all players
rp = RandomPlayer(g).play
gp = GreedyOthelloPlayer(g).play
hp = HumanOthelloPlayer(g).play

# nnet players
n1 = NNet(g)
n1.load_checkpoint('./pretrained_models/othello/pytorch/','6x100x25_best.pth.tar')
args1 = dotdict({'numMCTSSims': 50, 'cpuct':1.0})
mcts1 = MCTS(g, n1, args1)
n1p = lambda x: np.argmax(mcts1.getActionProb(x, temp=0))


#n2 = NNet(g)
#n2.load_checkpoint('/dev/8x50x25/','best.pth.tar')
#args2 = dotdict({'numMCTSSims': 25, 'cpuct':1.0})
#mcts2 = MCTS(g, n2, args2)
#n2p = lambda x: np.argmax(mcts2.getActionProb(x, temp=0))

arena = Arena.Arena(n1p, hp, g, display=display)
print(arena.playGames(2, verbose=True))
示例#2
0
any agent.
"""
with open('othello/book/XOT/openingssmall.txt') as my_file:
    book_array = my_file.readlines()

g = OthelloGame(8)

# all players
rp = RandomPlayer(g)
gp = GreedyOthelloPlayer(g)
hp = HumanOthelloPlayer(g)

edax = EdaxPlayer(3, g)

# nnet players
n1 = NNet(g)
n1.load_checkpoint('./temp/', 'restart.pth.tar')
#n1.load_checkpoint('./pretrained_models/othello/pytorch','restart.pth.tar')
args1 = dotdict({'numMCTSSims': 600, 'cpuct': 1.0})
n1p = NeuralPlayer(g, n1, args1)

n2 = NNet(g)
n2.load_checkpoint('./pretrained_models/othello/pytorch',
                   '8x8_100checkpoints_best.pth.tar')

args2 = dotdict({'numMCTSSims': 200, 'cpuct': 1.0})
n2p = NeuralPlayer(g, n2, args2, False)

arena = Arena.Arena(n1p, edax, g, display=display, book=book_array)
print(arena.playGames(10, verbose=True))