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Reimplementation of DDPG(Continuous Control with Deep Reinforcement Learning) based on OpenAI Gym + Tensorflow
| Date | Stars |
|---|---|
| 2026-07-31 | 574 |
| 2026-08-03 | 574 |
| 2026-08-04 | 574 |
| 2026-08-13 | 574 |
| 2026-08-14 | 574 |
| 2026-08-18 | 574 |
| 2026-08-22 | 575 |
| 2026-08-25 | 576 |
| 2026-09-18 | 576 |
| 2026-09-20 | 576 |
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# DDPG Reimplementing DDPG from Continuous Control with Deep Reinforcement Learning based on OpenAI Gym and Tensorflow [http://arxiv.org/abs/1509.02971](http://arxiv.org/abs/1509.02971) It is still a problem to implement Batch Normalization on the critic network. However the actor network works well with Batch Normalization. Some Mujoco environments are still unsolved on OpenAI Gym. ## Some Evaluations 1 [InvertedPendulum](https://gym.openai.com/evaluations/eval_mviLO6dZTCmtF1KSmprM1w#reproducibility) 2 [InvertedDoublePendulum](https://gym.openai.com/evaluations/eval_PtYUMaEUSwqS3YUYA6MOQ#reproducibility) 3 [Hopper unsolved](https://gym.openai.com/evaluations/eval_MwvKWh5CSp6SO8IAWU4pqw#reproducibility) ## How to use ``` git clone https://github.com/songrotek/DDPG.git cd DDPG python gym_ddpg.py ``` If you want to change the Gym environment, change ENV_NAME in gym_ddpg.py. If you want to change the Network type, change import in ddpg.py such as ``` from actor_network_bn import ActorNetwork to from actor_network import ActorNetwork ``` ## Reference 1 [https://github.com/rllab/rllab](https://github.com/rllab/rllab) 2 [https://github.com/MOCR/DDPG](https://github.com/MOCR/DDPG) 3 [https://github.com/SimonRamstedt/ddpg](https://github.com/SimonRamstedt/ddpg)
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:3a7477f3dc7b8681, desc:reinforcement learning