Explicitly show the relationships between various techniques of deep reinforcement learning methods. Dedicated for learning and researching on DRL.

Recommendations and suggestions are welcome.

• Rainbow: Combining Improvements in Deep Reinforcement Learning 6 Oct 2017
• Learning from Demonstrations for Real World Reinforcement Learning 12 Apr 2017
• Dueling Network Architecture
• Double DQN
• Prioritized Experience
• Deep Q-Networks

• Proximal Policy Optimization Algorithms 20 July 2017
• Emergence of Locomotion Behaviours in Rich Environments 7 July 2017
• Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning 1 Jun 2017
• 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

• The Uncertainty Bellman Equation and Exploration 15 Sep 2017
• Noisy Networks for Exploration 30 Jun 2017 implementation
• Count-Based Exploration in Feature Space for Reinforcement Learning 25 Jun 2017
• Count-Based Exploration with Neural Density Models 14 Jun 2017
• UCB and InfoGain Exploration via Q-Ensembles 11 Jun 2017
• Minimax Regret Bounds for Reinforcement Learning 16 Mar 2017
• Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models
• EX2: Exploration with Exemplar Models for Deep Reinforcement Learning

• 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

• Learning model-based planning from scratch 19 July 2017

• Imagination-Augmented Agents for Deep Reinforcement Learning 19 July 2017

• A Laplacian Framework for Option Discovery in Reinforcement Learning 16 Jun 2017

• Robust Imitation of Diverse Behaviors
• Learning human behaviors from motion capture by adversarial imitation
• Connecting Generative Adversarial Networks and Actor-Critic Methods

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

• Reinforcement Learning with Corrupted Reward Channel 23 May 2017

• Multi-step Reinforcement Learning: A Unifying Algorithm

• Neural Episodic Control

• TUNING RECURRENT NEURAL NETWORKS WITH REINFORCEMENT LEARNING

• Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments 10 Oct 2017
• Learning with Opponent-Learning Awareness 13 Sep 2017
• Counterfactual Multi-Agent Policy Gradients
• 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

• Reverse Curriculum Generation for Reinforcement Learning
• Trial without Error: Towards Safe Reinforcement Learning via Human Intervention
• Learning to Design Games: Strategic Environments in Deep Reinforcement Learning 5 July 2017

• Distral: Robust Multitask Reinforcement Learning 13 July 2017