强化学习族谱

https://github.com/tigerneil/deep-reinforcement-learning-family

deep-reinforcement-learning-records

Explicitly show the relationships between various techniques of deep reinforcement learning methods.

Dedicated for learning and researching on DRL.

Policy gradient methods

• Equivalence Between Policy Gradients and Soft Q-Learning
• Trust Region Policy Optimization
• Reinforcement Learning with Deep Energy-Based Policies
• Q-PROP: SAMPLE-EFFICIENT POLICY GRADIENT WITH AN OFF-POLICY CRITIC
• Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning 1 Jun 2017

Explorations in DRL

• Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models
• EX2: Exploration with Exemplar Models for Deep Reinforcement Learning

Actor-Critic methods

• The Reactor: A Sample-Efficient Actor-Critic Architecture 15 Apr 2017
• SAMPLE EFFICIENT ACTOR-CRITIC WITH EXPERIENCE REPLAY
• REINFORCEMENT LEARNING WITH UNSUPERVISED AUXILIARY TASKS
• Continuous control with deep reinforcement learning

Connection with other methods

• Connecting Generative Adversarial Networks and Actor-Critic Methods

Connecting value and policy methods

• Bridging the Gap Between Value and Policy Based Reinforcement Learning
• Policy gradient and Q-learning

Unifying

• Multi-step Reinforcement Learning: A Unifying Algorithm

Faster DRL

• Neural Episodic Control

Apply RL to other domains

• TUNING RECURRENT NEURAL NETWORKS WITH REINFORCEMENT LEARNING

Multiagent Settings

• Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments 7 Jun 2017
• Multiagent Bidirectionally-Coordinated Nets for Learning to Play StarCraft Combat Games 29 Mar 2017