我写了一个蒙特卡洛树搜索算法（基于https://en.wikipedia.org/wiki/Monte_Carlo_tree_search），并将它与“python-chess”库连接起来。
基本上，该算法卡在某个地方，因为它一直打印为输出“1/2-1/2”（绘图）。
扩展功能可能有问题，但我真的不知道在哪里。
这是代码：
class MonteCarloTreeSearch():
def __init__(self):
self.board = chess.Board()
self.results = []
self.total_matches = 0
def expansion(self, leaf):
done = False
if not (self.board.is_game_over()):
if len(leaf.children != 0):
possible = np.array([i for i in self.board.legal_moves])
actual = []
for i in range(len(possible)):
test = possible[i]
cnt = 0
for j in range(len(leaf.children)):
if (not test == leaf.children[j].value) and cnt == 0:
actual.append(test)
cnt += 1
move = random.choice(actual)
else:
move = random.choice([i for i in self.board.legal_moves])
self.board.push(move)
if self.board.is_game_over():
done = True
child = Node(move, player="white" if leaf.player=="black" else "black", parent=[leaf], score=0)
leaf.children = np.append(leaf.children, child)
if not done:
return self.expansion(child)
return leaf
def playout(self, starting_node):
childr = self.expansion(starting_node)
result = self.board.result()
if result == "1-0":
result = 1
elif result == "0-1":
result = -1
elif result == "1/2-1/2":
result = .5
elif result == "*":
raise Exception("ERROR: Game was not over, but playout stopped.")
else:
raise Exception("ERROR: Playout process error.")
return childr, result, starting_node
def expansion_playout_backpropagation(self, start):
node, result, starting_node = self.playout(start)
i = 0
while i == 0:
node.matches += 1
if node.player == "white":
if result == 1:
node.score += 1
if node.matches > 0:
node.winp = node.score / node.matches
else:
node.winp = 0
elif node.player == "black":
if result == -1:
node.score += 1
if node.matches > 0:
node.winp = node.score / node.matches
else:
node.winp = 0
else:
raise Exception("ERROR: Invalid player selection.")
if node.is_equal(starting_node):
i += 1
else:
node = node.parent[0]
self.results.append(self.board.result())
print(self.board.result())
self.board.reset_board()
self.total_matches += 1
def backpropagation(self, node, result, starting_node):
i = 0
while i == 0:
node.matches += 1
if node.player == "white":
if result == 1:
node.score += 1
if node.matches > 0:
node.winp = node.score / node.matches
else:
node.winp = 0
elif node.player == "black":
if result == -1:
node.score += 1
if node.matches > 0:
node.winp = node.score / node.matches
else:
node.winp = 0
else:
raise Exception("ERROR: Invalid player selection.")
if node.is_equal(starting_node):
i += 1
else:
node = node.parent[0]
self.results.append(self.board.result())
print(self.board.result())
self.board.reset_board()
self.total_matches += 1
def fitness(self, node):
p = node.winp
simulations = node.matches
parent_simulations = node.parent[0].matches if node.parent[0] != None else self.matches
c = math.sqrt(2)
if simulations > 0 and parent_simulations > 0:
formula = p + c * math.sqrt((np.log(parent_simulations)) / simulations)
else:
formula = p
return formula