An Option-Dependent Analysis of Regret Minimization Algorithms in Finite-Horizon Semi-Markov Decision Processes

no code implementations • 10 May 2023 • Gianluca Drappo, Alberto Maria Metelli, Marcello Restelli

Then, focusing on a sub-setting of HRL approaches, the options framework, we highlight how the average duration of the available options affects the planning horizon and, consequently, the regret itself.

Hierarchical Reinforcement Learning reinforcement-learning +1

Inverse Reinforcement Learning from a Gradient-based Learner

no code implementations • NeurIPS 2020 • Giorgia Ramponi, Gianluca Drappo, Marcello Restelli

Inverse Reinforcement Learning addresses the problem of inferring an expert's reward function from demonstrations.

reinforcement-learning Reinforcement Learning (RL)