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connect reversi with game

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This commit is contained in:
Dong Yan 2017-12-23 13:05:25 +08:00
parent 5b044c9a0c
commit e63338ab01
7 changed files with 57 additions and 40 deletions
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4
AlphaGo/engine.py
View File

@ -183,7 +183,7 @@ class GTPEngine():
return 'unknown player', False
def cmd_get_score(self, args, **kwargs):
return self._game.game_engine.executor_get_score(self._game.board, True), True
return self._game.game_engine.executor_get_score(self._game.board), True
def cmd_show_board(self, args, **kwargs):
return self._game.board, True
@ -194,4 +194,4 @@ class GTPEngine():
if __name__ == "main":
game = Game()
engine = GTPEngine(game_obj=Game)
engine = GTPEngine(game_obj=game)

44
AlphaGo/game.py
View File

@ -10,12 +10,14 @@ import copy
import tensorflow as tf
import numpy as np
import sys, os
import go
import model
from collections import deque
sys.path.append(os.path.join(os.path.dirname(__file__), os.path.pardir))
from tianshou.core.mcts.mcts import MCTS
import go
import reversi
class Game:
'''
Load the real game and trained weights.
@ -23,18 +25,26 @@ class Game:
TODO : Maybe merge with the engine class in future,
currently leave it untouched for interacting with Go UI.
'''
def __init__(self, size=9, komi=3.75, checkpoint_path=None):
self.size = size
self.komi = komi
self.board = [utils.EMPTY] * (self.size ** 2)
self.history = []
self.latest_boards = deque(maxlen=8)
for _ in range(8):
self.latest_boards.append(self.board)
self.evaluator = model.ResNet(self.size, self.size**2 + 1, history_length=8, checkpoint_path=checkpoint_path)
# self.evaluator = lambda state: self.sess.run([tf.nn.softmax(self.net.p), self.net.v],
# feed_dict={self.net.x: state, self.net.is_training: False})
self.game_engine = go.Go(size=self.size, komi=self.komi)
def __init__(self, name="go", checkpoint_path=None):
self.name = name
if "go" == name:
self.size = 9
self.komi = 3.75
self.board = [utils.EMPTY] * (self.size ** 2)
self.history = []
self.latest_boards = deque(maxlen=8)
for _ in range(8):
self.latest_boards.append(self.board)
self.evaluator = model.ResNet(self.size, self.size**2 + 1, history_length=8)
self.game_engine = go.Go(size=self.size, komi=self.komi)
elif "reversi" == name:
self.size = 8
self.evaluator = model.ResNet(self.size, self.size**2 + 1, history_length=1)
self.game_engine = reversi.Reversi()
self.board = self.game_engine.get_board()
else:
print(name + " is an unknown game...")
def clear(self):
self.board = [utils.EMPTY] * (self.size ** 2)
@ -65,7 +75,11 @@ class Game:
# this function can be called directly to play the opponent's move
if vertex == utils.PASS:
return True
res = self.game_engine.executor_do_move(self.history, self.latest_boards, self.board, color, vertex)
# TODO this implementation is not very elegant
if "go" == self.name:
res = self.game_engine.executor_do_move(self.history, self.latest_boards, self.board, color, vertex)
elif "revsersi" == self.name:
res = self.game_engine.executor_do_move(self.board, color, vertex)
return res
def think_play_move(self, color):
@ -96,7 +110,7 @@ class Game:
sys.stdout.flush()
if __name__ == "__main__":
g = Game(checkpoint_path='./checkpoints/')
g = Game()
g.show_board()
g.think_play_move(1)
#file = open("debug.txt", "a")

28
AlphaGo/go.py
View File

@ -157,7 +157,7 @@ class Go:
vertex = self._deflatten(action)
return vertex
def _is_valid(self, history_boards, current_board, color, vertex):
def _rule_check(self, history_boards, current_board, color, vertex):
### in board
if not self._in_board(vertex):
return False
@ -176,30 +176,30 @@ class Go:
return True
def simulate_is_valid(self, state, action):
def _is_valid(self, state, action):
history_boards, color = state
vertex = self._action2vertex(action)
current_board = history_boards[-1]
if not self._is_valid(history_boards, current_board, color, vertex):
if not self._rule_check(history_boards, current_board, color, vertex):
return False
if not self._knowledge_prunning(current_board, color, vertex):
return False
return True
def simulate_is_valid_list(self, state, action_set):
def simulate_get_mask(self, state, action_set):
# find all the invalid actions
invalid_action_list = []
invalid_action_mask = []
for action_candidate in action_set[:-1]:
# go through all the actions excluding pass
if not self.simulate_is_valid(state, action_candidate):
invalid_action_list.append(action_candidate)
if len(invalid_action_list) < len(action_set) - 1:
invalid_action_list.append(action_set[-1])
if not self._is_valid(state, action_candidate):
invalid_action_mask.append(action_candidate)
if len(invalid_action_mask) < len(action_set) - 1:
invalid_action_mask.append(action_set[-1])
# forbid pass, if we have other choices
# TODO: In fact we should not do this. In some extreme cases, we should permit pass.
return invalid_action_list
return invalid_action_mask
def _do_move(self, board, color, vertex):
if vertex == utils.PASS:
@ -219,7 +219,7 @@ class Go:
return [history_boards, new_color], 0
def executor_do_move(self, history, latest_boards, current_board, color, vertex):
if not self._is_valid(history, current_board, color, vertex):
if not self._rule_check(history, current_board, color, vertex):
return False
current_board[self._flatten(vertex)] = color
self._process_board(current_board, color, vertex)
@ -280,7 +280,7 @@ class Go:
elif color_estimate < 0:
return utils.WHITE
def executor_get_score(self, current_board, is_unknown_estimation=False):
def executor_get_score(self, current_board):
'''
is_unknown_estimation: whether use nearby stone to predict the unknown
return score from BLACK perspective.
@ -294,10 +294,8 @@ class Go:
_board[self._flatten(vertex)] = utils.BLACK
elif boarder_color == {utils.WHITE}:
_board[self._flatten(vertex)] = utils.WHITE
elif is_unknown_estimation:
_board[self._flatten(vertex)] = self._predict_from_nearby(_board, vertex)
else:
_board[self._flatten(vertex)] =utils.UNKNOWN
_board[self._flatten(vertex)] = self._predict_from_nearby(_board, vertex)
score = 0
for i in _board:
if i == utils.BLACK:

1
AlphaGo/play.py
View File

@ -7,7 +7,6 @@ import time
import os
import cPickle
class Data(object):
def __init__(self):
self.boards = []

16
AlphaGo/reversi.py
View File

@ -25,7 +25,6 @@ def find_correct_moves(own, enemy):
mobility |= search_offset_right(own, enemy, mask, 7) # Left bottom
return mobility
def calc_flip(pos, own, enemy):
"""return flip stones of enemy by bitboard when I place stone at pos.
@ -133,7 +132,9 @@ class Reversi:
self.board = self.bitboard2board()
return self.board
def simulate_is_valid(self, board, color):
def simulate_get_mask(self, state, action_set):
history_boards, color = state
board = history_boards[-1]
self.board = board
self.color = color
self.board2bitboard()
@ -142,13 +143,18 @@ class Reversi:
valid_moves = bit_to_array(mobility, 64)
valid_moves = np.argwhere(valid_moves)
valid_moves = list(np.reshape(valid_moves, len(valid_moves)))
return valid_moves
# TODO it seems that the pass move is not considered
invalid_action_mask = []
for action in action_set:
if action not in valid_moves:
invalid_action_mask.append(action)
return invalid_action_mask
def simulate_step_forward(self, state, vertex):
def simulate_step_forward(self, state, action):
self.board = state[0]
self.color = state[1]
self.board2bitboard()
self.vertex2action(vertex)
self.action = action
step_forward = self.step()
if step_forward:
new_board = self.bitboard2board()

2
AlphaGo/self-play.py
View File

@ -79,7 +79,7 @@ while True:
prob.append(np.array(game.prob).reshape(-1, game.size ** 2 + 1))
print("Finished")
print("\n")
score = game.game_engine.executor_get_score(game.board, True)
score = game.game_engine.executor_get_score(game.board)
if score > 0:
winner = utils.BLACK
else:

2
tianshou/core/mcts/mcts.py
View File

@ -73,7 +73,7 @@ class UCTNode(MCTSNode):
def valid_mask(self, simulator):
# let all invalid actions be illeagel in mcts
if self.mask is None:
self.mask = simulator.simulate_is_valid_list(self.state, range(self.action_num))
self.mask = simulator.simulate_get_mask(self.state, range(self.action_num))
self.ucb[self.mask] = -float("Inf")