62 citations · 134 across the 66 of their papers we have counts for
4 papers · 1 filter
Policy Space Identification in Configurable Environments
Alberto Maria Metelli, Guglielmo Manneschi, Marcello Restelli
We study the problem of identifying the policy space of a learning agent, having access to a set of demonstrations generated by its optimal policy. We introduce an approach based o…
Gradient-Aware Model-based Policy Search
Pierluca D'Oro, Alberto Maria Metelli, Andrea Tirinzoni +2
Traditional model-based reinforcement learning approaches learn a model of the environment dynamics without explicitly considering how it will be used by the agent. In the presence…
Feature Selection via Mutual Information: New Theoretical Insights
Mario Beraha, Alberto Maria Metelli, Matteo Papini +2
Mutual information has been successfully adopted in filter feature-selection methods to assess both the relevancy of a subset of features in predicting the target variable and the…
An Intrinsically-Motivated Approach for Learning Highly Exploring and Fast Mixing Policies
Mirco Mutti, Marcello Restelli
What is a good exploration strategy for an agent that interacts with an environment in the absence of external rewards? Ideally, we would like to get a policy driving towards a uni…