https://github.com/rlopensource/spinning_up_kr
https://github.com/rlopensource/spinning_up_kr
ddpg deep-deterministic-policy-gradient ou-noise ppo ppo2 proximal-policy-optimization reinforcement-learning robotics sac soft-actor-critic spinningup td3 trpo trust-region-policy-optimization
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/rlopensource/spinning_up_kr
- Owner: RLOpensource
- Created: 2019-03-27T07:44:17.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2019-04-02T21:52:00.000Z (over 6 years ago)
- Last Synced: 2025-04-15T21:48:45.683Z (6 months ago)
- Topics: ddpg, deep-deterministic-policy-gradient, ou-noise, ppo, ppo2, proximal-policy-optimization, reinforcement-learning, robotics, sac, soft-actor-critic, spinningup, td3, trpo, trust-region-policy-optimization
- Language: Python
- Size: 1.95 MB
- Stars: 6
- Watchers: 2
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Reconstruction of OpenAI spinningup for reinforcement-learning
* The purpose of this repository is study and research about reinforcement learning for robotics control.
* This repository provides the Model-Free reinforcement learning algorithms.
```
DDPG
TRPO
PPO
PPO2
SAC
TD3
```
* These algorithms are demonstrated in Environment Reacher with [ML-Agent](https://github.com/Unity-Technologies/ml-agents).
* The directory architecture have to be under format.
```
└─spinning_up_kr
├─env(environment of reacher in unity)
├─mlagents
├─buffer.py
├─core.py
├─ddpg.py
├─ou_noise.py
├─ppo.py
├─ppo2.py
├─sac.py
├─td3.py
└─trpo.py
```
## Demonstration
Reference
[1] [Proximal Policy Optimization](https://arxiv.org/abs/1707.06347)
[2] [High-Dimensional Continuous Control Using Generalized Advantage Estimation](https://arxiv.org/abs/1506.02438)
[3] [Continuous Control With Deep Reinforcement Learning](https://arxiv.org/pdf/1509.02971.pdf)
[4] [OpenAI Spinningup](https://github.com/openai/spinningup)
[5] [Reinforcement Learning Korea PG Travel](https://github.com/reinforcement-learning-kr/pg_travel)
[6] [Medipixel Reinforcement Learning Repository](https://github.com/medipixel/rl_algorithms)
[7] [Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor](https://arxiv.org/abs/1801.01290)
[8] [tensorflow reinforcement learning framework](https://github.com/RLOpensource/tensorflow_RL)
[9] [Trust Region Policy Optimization](https://arxiv.org/abs/1502.05477)
[10] [Addressing Function Approximation Error in Actor-Critic Methods](https://arxiv.org/abs/1802.09477)