Key Papers in Deep RL — Spinning Up documentation
What follows is a list of papers in deep RL that are worth reading. This is far from comprehensive, but should provide a useful starting point for someone looking to do research in the field. Table of Contents © Copyright 2018, OpenAI. Revision 038665d6.
Key Papers in Deep RL - Spinning Up documentation --> Docs >> Key Papers in Deep RL Edit on GitHub Key Papers in Deep RL ¶ What follows is a list of papers in deep RL that are worth reading. This is far from comprehensive, but should provide a useful starting point for someone looking to do research in the field. Table of Contents Key Papers in Deep RL 1. Model-Free RL 2. Exploration 3. Transfer and Multitask RL 4. Hierarchy 5. Memory 6. Model-Based RL 7. Meta-RL 8. Scaling RL 9. RL in the Real World 10. Safety 11. Imitation Learning and Inverse Reinforcement Learning 12. Reproducibility, Anal
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