强化学习基础 Ⅳ: State-of-the-art 强化学习经典算法汇总 (知乎转载)

为了让大家对 RL 的 SOTA 算法有一个直观的概念，我重新整理了一下 SOTA 算法目录，有些我已经在self-implement，有些写了相关的paper reading.

Model-free

Value-based

1. Q-learning
   [ Paper | Code | Blog | 1992 ]

2. Sarsa, Sarsa(  )
   [ Paper | Code | Blog | 1994 ]

3. Deep Q Network (DQN)
   [ Paper | Code | Blog | 2015 ]

4. Double Deep Q Network
   [ Paper | Code | Blog | 2015 ]

5. Dueling Deep Q Network
   [ Paper | Code | Blog | 2015 ]

6. Double Dueling Deep Q Network (D3QN)
   [ No Paper | Code | Blog | 2015 ]

7. Rainbow
   [ Paper | Code | Blog | 2017 ]

8. Hindsight Experience Replay(HER) (也可用于DDPG)
   [ Paper | Code | Blog | 2017 ]

Policy-based

1. Vanilla Policy Gradient / REINFORCE
   [ Paper | Code | Blog | 2000 ]

2. Trust Region Policy Optimization (TRPO)
   [ Paper | Code | Blog | 2015 ]

3. Proximal Policy Optimization (PPO)
   [ Paper | Code | Blog | 2017 ]

Actor-Critic

1. Actor-Critic
   [ Paper | Code pytorch | Blog | 2000 ]

2. Advantage Actor-Critic (A2C)
   [ No Paper | Code | Blog | 未知 ]

3. Deep Deterministic Policy Gradient (DDPG)
   [ Paper | Code1 OpenAI | Code2 | Blog | 2015 ]

4. Twin Delayed DDPG (TD3)
   [ Paper | Code | Blog | 2018 ]

5. Soft Actor-Critic (SAC)
   [ Paper | Code tf | Blog | 2018 ]

Model-based

1. Dyna
   [ Paper | Code | Blog | 1991 ]

2. PILCO
   [ Paper | Code | Blog | 2011 ]

3. Value Prediction Network (VPN)
   [ Paper | Code | Blog | 2018 ]

4. Guided Policy Search (GPS)
   [ Paper | Code | Blog | 2017 ]

5. Model-Based Value Expansion (MVE)
   [ Paper | Code | Blog | 2018 ]

6. Stochastic Ensemble Value Expansion (STEVE)
   [ Paper | Code | Blog | 2018 ]

7. Model-Based Policy Optimization (MBPO)
   [ Paper | Code | Blog | 2019 ]

Hierarchical RL

1. Hierarchical DQN (h-DQN)
   [ Paper | Code Keras | Code pytorch | Blog | 2016 ]

2. Hierarchical DDPG (h-DDPG)
   [ Paper | Code | Blog | 2017 ]

3. Hierarchical-Actor-Critic (HAC)
   [ Paper | Code pytorch | Code TF | Blog_CN | Blog_EG | 2019 ]

Distributed Architecture

1. Asynchronous Advantage Actor-Critic (A3C)
   [ Paper | Code pytorch | Blog | 2016 ]

2. Distributed PPO (DPPO)
   [ Paper | Code pytorch | Blog | 2017 ]

3. IMPALA
   [ Paper | Code | Blog | 2018 ]

4. APE-X
   [ Paper | Code | Blog | 2018 ]

5. Divergence-augmented Policy Optimization (DAPO)
   [ Paper | Code | Blog | 2019 ]

Multi-Agent

1. Value-Decomposition Networks (VDN)
   [ Paper | Code | Blog | 2017 ]

2. MADDPG
   [ Paper | Code OpenAI | Blog | 2017 ]

3. Mean Field Multi-Agent RL
   [ Paper | Code | Blog | 2018 ]

4. QMIX
   [ Paper | Code | Blog | 2018 ]

5. Actor-Attention-Critic for Multi-Agent (MAAC)
   [ Paper | Code | Blog | 2018 ]

链接有误，烦请告知，不胜感激

更多算法实现见本专栏关联Github

Machine-Learning-is-ALL-You-Needgithub.com

欢迎 Watch & Star !!!!!

本文转载自：https://zhuanlan.zhihu.com/p/137208923