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drl-tensorflow's Introduction

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2020-12-09

发现这是我获得star最多的一个项目了。

刚才过了一遍所有的文件,发现优先经验回放PER没有单独抽取出来,还是和DDPG打包在一起的,这样会导致不能和TD3,SAC兼容。

另外sac-auto也没有提交。

事后经验回放HER没有实现(我到现在还没有调出最好的参数,贼烦,我本以为her是灵丹妙药,没想到不过如此)。

另外继续搞tf1感觉有种49年入国军的错觉。

难顶

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DRL-tensorflow

My DRL library with tensorflow1.14 core codes based on https://github.com/openai/spinningup

My job is wrap the algorithms functions into classes in order to easy to call. Maintain the performance in gym environments of the original codes.

越来越丰富了,基本上将主流的深度强化学习的off-policy的三个主要算法都打包成功了。 目前都是最简单的模式,直接进入algo_class.py的文件中,run就完事儿了。

对于结果的显示,以及性能的对比,目前做的还不够,因为我还没吃透spinning-up的log类,没有办法更方便的将这个功能嵌入进去。 还有画图的功能,目前只能用乞丐版的matplotlib画个图。

等我有时间了再加点功能~


已经更新了logger和plot功能,功能实现代码在sp_utils文件夹中,直接抽调了spinup的代码,做了稍许修改。 在run_in_gym这个文件夹中可以直接试用该功能,非常方便。 spinup的这两个功能可以抽调到大家自己开发的包当中,比自己实现要省事儿很多。

另外,个人感觉我封装的这三个算法,好像不是特别的完美,在gym中测试好像没有问题,但是在机器人环境中无法收敛。 要是有人测试出bug的话,恳请告知~


大家要是用起来有什么bug,欢迎开issues~ 要是有帮助的话,希望能给个star。

过段时间看看能不能加个LSTM的,我已经看到有大佬的实现了,整合一下到我这个包里~

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