QLearning.py 文件源码

def learn(self):
        y, x = self.state
    current_acton_list = copy.deepcopy(self.action_list[y,x])
    if np.random.rand() > self.epsilon:
            max_q = self.q[current_acton_list,y,x].max()
        action_list_index = list(np.argwhere(self.q[current_acton_list,y,x] == max_q))
        random.shuffle(action_list_index)
            action = current_acton_list[action_list_index[0]]
    else:
        random.shuffle(current_acton_list)
            action = current_acton_list[0]
        move = self.move_list.get(action)
    self.update_q(action, move)
        self.q_value_list.append(self.q_max_value(move))
        self.state += move