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cs.LG2024
A Bayesian Solution To The Imitation Gap
Risto Vuorio, Mattie Fellows, Cong Lu +2
In many real-world settings, an agent must learn to act in environments where no reward signal can be specified, but a set of expert demonstrations is available. Imitation learning…
cs.LG2023
Bayesian Exploration Networks
Mattie Fellows, Brandon Kaplowitz, Christian Schroeder de Witt +1
Bayesian reinforcement learning (RL) offers a principled and elegant approach for sequential decision making under uncertainty. Most notably, Bayesian agents do not face an explora…
cs.LG2023
Why Target Networks Stabilise Temporal Difference Methods
Mattie Fellows, Matthew J. A. Smith, Shimon Whiteson
Integral to recent successes in deep reinforcement learning has been a class of temporal difference methods that use infrequently updated target values for policy evaluation in a M…