def search(state, alpha, beta):
if (time() - start_time) >= self.max_time:
return -1
player = State.opponent(state.player)
moves = state.board.legal_moves(player)
if state.depth == plies or len(moves) == 0:
self.evaluate(state)
else:
for move in moves:
next_board = deepcopy(state.board)
next_board.make_move(move[0], move[1], player)
next_state = GameState(next_board,
parent=state,
player=player,
depth=state.depth+1,
move=move)
ret = search(next_state, alpha, beta)
if ret == -1:
return ret
if state.player is State.black:
alpha = max(alpha, next_state.score)
state.score = alpha
else:
beta = min(beta, next_state.score)
state.score = beta
if alpha >= beta:
break
state.children[move] = next_state
def move(self, board):
start_time = time()
best_move = None
plies = 0
max_plies = 64 - board.total_count()
while True:
plies += 1
if plies > max_plies or (time() - start_time) >= self.max_time:
return best_move
def search(state, alpha, beta):
if (time() - start_time) >= self.max_time:
return -1
player = State.opponent(state.player)
moves = state.board.legal_moves(player)
if state.depth == plies or len(moves) == 0:
self.evaluate(state)
else:
for move in moves:
next_board = deepcopy(state.board)
next_board.make_move(move[0], move[1], player)
next_state = GameState(next_board,
parent=state,
player=player,
depth=state.depth+1,
move=move)
ret = search(next_state, alpha, beta)
if ret == -1:
return ret
if state.player is State.black:
alpha = max(alpha, next_state.score)
state.score = alpha
else:
beta = min(beta, next_state.score)
state.score = beta
if alpha >= beta:
break
state.children[move] = next_state
initial_player = State.opponent(self.color)
current_state = GameState(board, depth=0, player=initial_player)
ret = search(current_state, float("-inf"), float("inf"))
if ret == -1:
return best_move
scores = [(s.score, m) for m, s in current_state.children.items()]
if len(scores) == 0:
# pass
return None
if self.color is State.black:
best_score, best_move = max(scores)
else:
best_score, best_move = min(scores)
s = "abcdefgh"[best_move[1]] + str(best_move[0] + 1)
print("Searched {} plies and got {} ({})".format(plies,
s,
best_score))
return best_move
