Awesome Open Source
Awesome Open Source

Awesome Deep Reinforcement Learning

Landscape of Deep RL

updated Landscape of DRL

This project is built for people who are learning and researching on latest deep reinforcement learning methods.

Content

Illustrations:

Recommendations and suggestions are welcome.

General guidances

Foundations and theory

General benchmark frameworks

Value based

Policy gradient

Explorations

Actor-Critic

Model-based

Model-free + Model-based

Hierarchical

Option

Connection with other methods

Connecting value and policy methods

Reward design

Unifying

Faster DRL

Multi-agent

New design

Multitask

Observational Learning

Meta Learning

Distributional

Planning

Safety

Inverse RL

No reward RL

Time

Adversarial learning

Use Natural Language

Generative and contrastive representation learning

Belief

PAC

Applications


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