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Shangtong Zhang
2017-10-06 22:10:44 -06:00
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@@ -49,14 +49,25 @@ variance unbounded, which is also included in the implementation.
## DDPG
![Loading...](https://raw.githubusercontent.com/ShangtongZhang/DeepRL/master/images/DDPG-Pendulum-v0.png)
DDPG is extremely unstable and is the most difficult algorithm to tune from my experience. And it cannot solve
Continuous Lunar Lander or Bipedal Walker. I never see a public DDPG implementation without a fixed random seed
that can solve tasks other than the family of Pendulum. If you find a bug or some successful practice, it will
be much appreciated to let me know that.
## DPPO
The difference between my implementation and [DeepMind version](https://arxiv.org/abs/1707.02286) is:
![Loading...](https://raw.githubusercontent.com/ShangtongZhang/DeepRL/master/images/DPPO.png)
The difference between my implementation and [DeepMind's DPPO](https://arxiv.org/abs/1707.02286) is:
1. PPO stands for different algorithms.
2. I use a much simpler A3C-like synchronization protocol.
The body of PPO is based on [this](https://github.com/alexis-jacq/Pytorch-DPPO), however that implementation has some
critical bugs.
I use 8 threads and a two tanh hidden layer network, each hidden layer has 64 hidden units.
# Dependency
* Open AI gym