DQN PYTORCH 玩FlappyBird

import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
# import gym

from ple.games.flappybird import FlappyBird
from ple import PLE
from pygame.constants import K_w
import time
import random
import collections
import numpy as np
import os

# Hyper Parameters
BATCH_SIZE = 32
LR = 0.0001                 # learning rate
EPSILON = 0.9               # greedy policy
GAMMA = 0.999                 # reward discount
TARGET_REPLACE_ITER = 100   # target update frequency
MEMORY_CAPACITY = 20000

game = FlappyBird()
env = PLE(game, fps=30, display_screen=True)

N_ACTIONS =2# env.action_space.n
N_STATES = 8#env.observation_space.shape[0]


class Net(nn.Module):
    def __init__(self, ):
        super(Net, self).__init__()
        self.fc1 = nn.Linear(N_STATES, 128)
        self.fc1.weight.data.normal_(0, 0.
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值