64 lines
2.3 KiB
Python
64 lines
2.3 KiB
Python
#!/usr/bin/env python
|
|
# coding=utf-8
|
|
'''
|
|
Author: John
|
|
Email: johnjim0816@gmail.com
|
|
Date: 2020-09-11 23:03:00
|
|
LastEditor: John
|
|
LastEditTime: 2021-12-22 10:54:57
|
|
Discription: use defaultdict to define Q table
|
|
Environment:
|
|
'''
|
|
import numpy as np
|
|
import math
|
|
import torch
|
|
from collections import defaultdict
|
|
|
|
class QLearning(object):
|
|
def __init__(self,
|
|
n_actions,cfg):
|
|
self.n_actions = n_actions
|
|
self.lr = cfg.lr # 学习率
|
|
self.gamma = cfg.gamma
|
|
self.epsilon = cfg.epsilon_start
|
|
self.sample_count = 0
|
|
self.epsilon_start = cfg.epsilon_start
|
|
self.epsilon_end = cfg.epsilon_end
|
|
self.epsilon_decay = cfg.epsilon_decay
|
|
self.Q_table = defaultdict(lambda: np.zeros(n_actions)) # 用嵌套字典存放状态->动作->状态-动作值（Q值）的映射，即Q表
|
|
def sample(self, state):
|
|
''' 采样动作，训练时用
|
|
'''
|
|
self.sample_count += 1
|
|
self.epsilon = self.epsilon_end + (self.epsilon_start - self.epsilon_end) * \
|
|
math.exp(-1. * self.sample_count / self.epsilon_decay) # epsilon是会递减的，这里选择指数递减
|
|
# e-greedy 策略
|
|
if np.random.uniform(0, 1) > self.epsilon:
|
|
action = np.argmax(self.Q_table[str(state)]) # 选择Q(s,a)最大对应的动作
|
|
else:
|
|
action = np.random.choice(self.n_actions) # 随机选择动作
|
|
return action
|
|
def predict(self,state):
|
|
''' 预测或选择动作，测试时用
|
|
'''
|
|
action = np.argmax(self.Q_table[str(state)])
|
|
return action
|
|
def update(self, state, action, reward, next_state, done):
|
|
Q_predict = self.Q_table[str(state)][action]
|
|
if done: # 终止状态
|
|
Q_target = reward
|
|
else:
|
|
Q_target = reward + self.gamma * np.max(self.Q_table[str(next_state)])
|
|
self.Q_table[str(state)][action] += self.lr * (Q_target - Q_predict)
|
|
def save(self,path):
|
|
import dill
|
|
torch.save(
|
|
obj=self.Q_table,
|
|
f=path+"Qleaning_model.pkl",
|
|
pickle_module=dill
|
|
)
|
|
print("保存模型成功！")
|
|
def load(self, path):
|
|
import dill
|
|
self.Q_table =torch.load(f=path+'Qleaning_model.pkl',pickle_module=dill)
|
|
print("加载模型成功！") |