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20242026
most citedModel-Free Active Exploration in Reinforcement Learning

2 citations · 2 across the 10 of their papers we have counts for

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cs.LG2024

Efficient Learning of POMDPs with Known Observation Model in Average-Reward Setting

Alessio Russo, Alberto Maria Metelli, Marcello Restelli

Dealing with Partially Observable Markov Decision Processes is notably a challenging task. We face an average-reward infinite-horizon POMDP setting with an unknown transition model…

cs.LG2024★ 2 cited

Model-Free Active Exploration in Reinforcement Learning

Alessio Russo, Alexandre Proutiere

We study the problem of exploration in Reinforcement Learning and present a novel model-free solution. We adopt an information-theoretical viewpoint and start from the instance-spe…