可以提供一个Q-learning的智能体的代码吗？

逃离我推掉我的手 2024-03-27 12:52 39阅读 0赞

当然可以! 下面是一个简单的 Q-learning 智能体的 Python 代码例子：

import numpyas np
    
    class QLearningAgent:
        def __init__(self, alpha, epsilon, discount, get_legal_actions):
            self.get_legal_actions = get_legal_actions
            self._qvalues = {}
            self.alpha = alpha
            self.epsilon = epsilon
            self.discount = discount
    
        def get_qvalue(self, state, action):
            return self._qvalues.get((state, action), 0.0)
    
        def set_qvalue(self, state, action, value):
            self._qvalues[(state, action)] = value
    
        def get_value(self, state):
            possible_actions = self.get_legal_actions(state)
            if not possible_actions:
                return 0.0
            return max(self.get_qvalue(state, action) for action in possible_actions)
    
        def update(self, state, action, reward, next_state):
            gamma = self.discount
            learning_rate = self.alpha
            q_next = self.get_value(next_state)
            q_current = self.get_qvalue(state, action)
            self.set_qvalue(state, action, q_current + learning_rate * (reward + gamma * q_next - q_current))
    
        def get_best_action(self, state):
            possible_actions = self.get_legal_actions(state)
            if not possible_actions:
                return None
            best_action = max(possible_actions, key=lambda x: self.get_qvalue(state, x))
            return best_action
    
        def get_action(self, state):
            possible_actions = self.get_legal_actions(state)
            if not possible_actions:
                return None
    
            if np.random.rand() < self.epsilon:
                return np.random.choice(possible_actions)
            return self.get_best_action(state)

希望这个代码能帮助到你！