238 citations · 642 across the 25 of their papers we have counts for
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cs.LG2019★ 27 cited
A Geometric Perspective on Optimal Representations for Reinforcement Learning
Marc G. Bellemare, Will Dabney, Robert Dadashi +6
We propose a new perspective on representation learning in reinforcement learning based on geometric properties of the space of value functions. We leverage this perspective to pro…
cs.LG2019★ 12 cited
The Value Function Polytope in Reinforcement Learning
Robert Dadashi, Adrien Ali Taïga, Nicolas Le Roux +2
We establish geometric and topological properties of the space of value functions in finite state-action Markov decision processes. Our main contribution is the characterization of…