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scripts/train_dizhu_model.py

@@ -0,0 +1,46 @@
+from stable_baselines3 import PPO
+from src.environment.dizhu_env import DouDiZhuEnv  # 导入斗地主环境
+import torch
+from configs.log_config import setup_logging
+from loguru import logger  # 添加 logger
+
+def train_dizhu_model():
+    # 创建 DouDiZhuEnv 环境实例
+    env = DouDiZhuEnv()
+
+    # 检查是否有可用的 GPU
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    logger.info(f"使用设备: {device}")  # 使用 logger 记录设备信息
+
+    # 使用 PPO 算法训练模型，设置为 MultiInputPolicy
+    model = PPO(
+        "MultiInputPolicy",  # 适用于多输入的策略
+        env,
+        verbose=1,
+        tensorboard_log="../logs/ppo_doudizhu_tensorboard/",  # TensorBoard 日志路径
+        device=device
+    )
+
+    # 训练模型，设定总训练步数
+    logger.info("开始训练斗地主模型...")
+    model.learn(total_timesteps=100000)  # 总训练步数
+    logger.info("斗地主模型训练完成！")
+
+    # 保存训练后的模型
+    model_path = "../models/ppo_doudizhu_model"
+    model.save(model_path)
+    logger.info(f"模型已保存到 '{model_path}'")
+
+    # 测试模型
+    logger.info("开始测试斗地主模型...")
+    obs = env.reset()
+    done = False
+    while not done:
+        action, _states = model.predict(obs)  # 使用训练好的模型来选择动作
+        obs, reward, done, info = env.step(action)  # 执行动作
+        logger.info(f"动作: {action}, 奖励: {reward}, 是否结束: {done}, 信息: {info}")  # 记录测试过程
+
+if __name__ == "__main__":
+    # 设置日志
+    setup_logging()
+    train_dizhu_model()

src/engine/dizhu/dizhu_engine.py

@@ -36,23 +36,28 @@ class DiZhuEngine:
 
     def step(self, action):
         """
-        执行玩家的出牌动作。
+        执行动作并更新状态
-        :param action: 当前玩家的动作（出牌或过牌）
+        :param action: 当前玩家的动作（可以是 'pass' 或一个动作列表）
         """
         current_player = self.get_current_player()
 
         if action == "pass":
-            # 玩家选择过牌
+            # 过牌作为单独的历史记录
-            current_player.history.append("pass")
+            current_player.history.append([])
         else:
-            # 玩家出牌，移除对应牌
+            # 确保动作始终为列表
+            if not isinstance(action, list):
+                action = [action]
+            # 检查动作合法性
             if not all(card in current_player.hand_cards for card in action):
-                raise ValueError("玩家手牌不足以完成此次出牌")
+                raise ValueError(f"玩家手牌不足以完成此次出牌: {action}")
+            # 移除出牌
             for card in action:
                 current_player.hand_cards.remove(card)
+            # 记录动作
             current_player.history.append(action)
 
-        # 检查是否游戏结束
+        # 检查游戏是否结束
         if not current_player.hand_cards:
             self.game_over = True
             return f"{current_player.role} 胜利！"
@@ -60,6 +65,7 @@ class DiZhuEngine:
         # 切换到下一个玩家
         self.current_player_index = (self.current_player_index + 1) % 3
 
+
     def get_game_state(self):
         """
         返回当前游戏状态，包括玩家手牌、出牌历史和当前玩家。

src/engine/dizhu/player_state.py

@@ -1,5 +1,7 @@
+from collections import deque
+
 class PlayerState:
     def __init__(self, hand_cards, role):
         self.hand_cards = hand_cards  # 玩家手牌
         self.role = role  # "地主" 或 "农民"
-        self.history = []  # 出牌历史
+        self.history = deque()  # 出牌历史，使用 deque

src/environment/dizhu_env.py

@@ -40,14 +40,22 @@ class DouDiZhuEnv(gym.Env):
     def _get_observation(self):
         """获取当前玩家的状态"""
         current_player = self.engine.get_current_player()
+
+        # 手牌的独热编码
         hand_cards = np.zeros(54, dtype=np.int32)
         for card in current_player.hand_cards:
             hand_cards[card] = 1
 
+        # 出牌历史的独热编码
         history = np.zeros(54, dtype=np.int32)
         for play in current_player.history:
-            for card in play:
+            if isinstance(play, list):  # 如果是列表
-                history[card] = 1
+                for card in play:
+                    history[card] = 1
+            elif isinstance(play, int):  # 如果是单个牌
+                history[play] = 1
+            else:
+                raise ValueError(f"历史记录格式错误: {play}")
 
         return {"hand_cards": hand_cards, "history": history}