Distributed Deep Reinforcement Learning by Ray and TensorFlow.
This framework inspired by general-purpose RL training system Rapid from OpenAI.
Rapid framework:
This framework:
Tutorial (Chinese version)
- Parallelize your algorithm by Ray (1)
- Parallelize your algorithm by Ray (2)
- Parallelize your algorithm by Ray (3)
In short. This framework divides the reinforcement learning process into five parts:
- Replay buffer (option)
- Parameter server
- train (learn)
- rollout
- test
简单实验对比：
实验：LunarLanderContinuous-v2
算法：SAC
未调参，sac和dsac参数相同，dsac的worker数量：1。GPU：GTX1060
(dsac: distributed sac)
