3 citations · 3 across the 3 of their papers we have counts for
3 papers
A Provably Efficient Option-Based Algorithm for both High-Level and Low-Level Learning
Gianluca Drappo, Alberto Maria Metelli, Marcello Restelli
Hierarchical Reinforcement Learning (HRL) approaches have shown successful results in solving a large variety of complex, structured, long-horizon problems. Nevertheless, a full th…
An Option-Dependent Analysis of Regret Minimization Algorithms in Finite-Horizon Semi-Markov Decision Processes
Gianluca Drappo, Alberto Maria Metelli, Marcello Restelli
A large variety of real-world Reinforcement Learning (RL) tasks is characterized by a complex and heterogeneous structure that makes end-to-end (or flat) approaches hardly applicab…
Inverse Reinforcement Learning from a Gradient-based Learner
Giorgia Ramponi, Gianluca Drappo, Marcello Restelli
Inverse Reinforcement Learning addresses the problem of inferring an expert's reward function from demonstrations. However, in many applications, we not only have access to the exp…