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NIPS 2020 Reinforcement Learning Paper: Imitation Learning

NIPS 2020 Reinforcement Learning Paper: Imitation Learning

We pick some papers about imitation learning in nips 2020 to annotate.

Offline Imitation Learning with a Misspecified Simulator

This work investigate policy learning in the condition of a few expert demonstrations and a simulator with misspecified dynamics.

Story: There are two current approaches to apply RL in real-world without a costly trial-and-error process: imitation learning and to train a policy in a simulator. This paper images a feasible scenario that we have a few expert demonstrations and a simulator with misspecified dynamics.

Extensive-Form

Extensive-Form Fictitious Play

References

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