强化学习--Pytorch--DQN

DQN的学习效果还是很惊艳的，首先放上本次实验的代码。和官方给出的例子一样，是托举平衡杆的问题。
给出视频链接：强化学习DQN

import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from torch.autograd import Variable
import gym
 
# 超参数
BATCH_SIZE = 32
LR = 0.01  # learning rate
# 强化学习的参数
EPSILON = 0.9  # greedy policy
GAMMA = 0.9  # reward discount
TARGET_REPLACE_ITER = 200  # target update frequency
MEMORY_CAPACITY = 2000
# 导入实验环境
env = gym.make('CartPole-v0')
env = env.unwrapped
N_ACTIONS = env.action_space.n
N_STATES = env.observation_space.shape[0]
 
 
class Net(nn.Module):
    def __init__(self, ):
        super(Net, self).__init__()
        self.fc1 = nn.Linear(N_STATES, 10)
        self.fc1.weight.data.normal_(0, 0.1)  # 初始化
        self.out = nn.Linear(10, N_ACTIONS)
        self.out.weight.data.normal_(0, 0.1)  # 初始化
 
    def forward(self