27 citations · 39 across the 2 of their papers we have counts for
4 papers
Zooming for Efficient Model-Free Reinforcement Learning in Metric Spaces
Ahmed Touati, Adrien Ali Taiga, Marc G. Bellemare
Despite the wealth of research into provably efficient reinforcement learning algorithms, most works focus on tabular representation and thus struggle to handle exponentially or in…
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…
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…
Approximate Exploration through State Abstraction
Adrien Ali Taïga, Aaron Courville, Marc G. Bellemare
Although exploration in reinforcement learning is well understood from a theoretical point of view, provably correct methods remain impractical. In this paper we study the interpla…