Search Results for author: Michel Ma

Found 3 papers, 2 papers with code

Do Transformer World Models Give Better Policy Gradients?

no code implementations7 Feb 2024 Michel Ma, Tianwei Ni, Clement Gehring, Pierluca D'Oro, Pierre-Luc Bacon

We integrate such AWMs into a policy gradient framework that underscores the relationship between network architectures and the policy gradient updates they inherently represent.


When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment

2 code implementations NeurIPS 2023 Tianwei Ni, Michel Ma, Benjamin Eysenbach, Pierre-Luc Bacon

The Transformer architecture has been very successful to solve problems that involve long-term dependencies, including in the RL domain.

Reinforcement Learning (RL)

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