Comments (1)
NikuKikai
commented on July 28, 2024
关于网络
强化学习的最普遍的结构 Actor Critic，可以参考A3C的原论文以及OpenAI的Baselines里的实现。
这里的subnet是Actor网络和Critic网络共享的部分，输入通过subnet后再分别输入Actor和Critc，意思是subnet对输入抽象之后再分别用来算Action和Value。当然对于这种简单的问题，直接A和C两个网络也完全没问题。
place_len ?
我这里是把道路离散化了。训练会比较容易。
每place_len=7.5m 长度作为一个place，整条道路的状态就是若干个place构成的一个向量。
每个位的值表示每个place里面有多少车（当然可以是小数
其他
另外我不太记得github上的这个程序是不是真的能学的了，后面做的都没有上传。
还有就是这个太早了，用的tensorflow1.4，用现在的tensorflow2的keras写应该会清晰很多。
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