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dqn-pytorch's Introduction

DQN PyTorch

This is a simple implementation of the Deep Q-learning algorithm on the Atari Pong environment.

References

  1. Playing Atari with Deep Reinforcement Learning, Mnih et al., 2013

dqn-pytorch's People

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dqn-pytorch's Issues

Don‘t converge

After 400 epochs of training, the total rewards keeps -21.0~-19.0 and takes about 800-1200 steps for a round.
Anyone has met this problem? Any idea of solving this?
environ:
pytorch 1.5
python 3.7
gym 0.17.3
atari_py 0.2.6
ubuntu 16.04

重复开局

从该作者提供的 pong.gif 可以看出智能体的动作出现了循环,原因是对手方的程序固定,存在漏洞,智能体找到这个漏洞进行加强,那么如果对手方是人类,能够正常运行吗?
另,哪里下载权重文件,没找到,只能自己训练。

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