1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 1 cited
The Limits of Pure Exploration in POMDPs: When the Observation Entropy is Enough
Riccardo Zamboni, Duilio Cirino, Marcello Restelli +1
The problem of pure exploration in Markov decision processes has been cast as maximizing the entropy over the state distribution induced by the agent's policy, an objective that ha…
cs.LG2024
How to Explore with Belief: State Entropy Maximization in POMDPs
Riccardo Zamboni, Duilio Cirino, Marcello Restelli +1
Recent works have studied *state entropy maximization* in reinforcement learning, in which the agent's objective is to learn a policy inducing high entropy over states visitation (…