Uploaded June 2023 | Updated September 2026, 2 hours ago

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Reinforcement learning is great, but environment interaction can be expensive. This paper proposes an RL algorithm based of successor features that takes advantage of passive data to learn about the world without acting itself.

Outline
0:00 - Intro
1:41 - Offline-RL
2:50 - Successor Features
13:34 - Algorithm
21:11 - Results
27:50 - Criticisms & Thoughts

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Sources:
Paper - arxiv.org/pdf/2304.04782.pdf