问题描述
我编写了一种基于https://en.wikipedia.org/wiki/Monte_Carlo_tree_search的蒙特卡洛树搜索算法，并将其与“ python-chess”库相连接。
基本上，该算法卡在了某处，因为它一直将输出作为输出“ 1 / 2-1 / 2”（绘制）。
扩展功能可能存在问题，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,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,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
解决方法
暂无找到可以解决该程序问题的有效方法，小编努力寻找整理中！
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