3 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 2 cited
A Kernel Perspective on Behavioural Metrics for Markov Decision Processes
Pablo Samuel Castro, Tyler Kastner, Prakash Panangaden +1
Behavioural metrics have been shown to be an effective mechanism for constructing representations in reinforcement learning. We present a novel perspective on behavioural metrics f…
cs.GT2022★ 2 cited
Learning Correlated Equilibria in Mean-Field Games
Paul Muller, Romuald Elie, Mark Rowland +7
The designs of many large-scale systems today, from traffic routing environments to smart grids, rely on game-theoretic equilibrium concepts. However, as the size of an -player…
cs.LG2022★ 3 cited
The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement Learning
Yunhao Tang, Mark Rowland, Rémi Munos +3
We study the multi-step off-policy learning approach to distributional RL. Despite the apparent similarity between value-based RL and distributional RL, our study reveals intriguin…