Tommaso Giorgi

Impact of Connectivity on Laplacian Representations in Reinforcement Learning

Learning state representations in Markov Decision Processes (MDPs) has proven crucial for addressing the curse of dimensionality in large-scale reinforcement learning (RL) problems. A widely recognized approach exploits structural priors on the MDP by constructing state representations as linear com…