2 papers
cs.LG2026
Impact of Connectivity on Laplacian Representations in Reinforcement Learning
Tommaso Giorgi, Pierriccardo Olivieri, Keyue Jiang +2
Learning compact state representations in Markov Decision Processes (MDPs) has proven crucial for addressing the curse of dimensionality in large-scale reinforcement learning (RL)…
cs.AI2026
Do It for HER: First-Order Temporal Logic Reward Specification in Reinforcement Learning (Extended Version)
Pierriccardo Olivieri, Fausto Lasca, Alessandro Gianola +1
In this work, we propose a novel framework for the logical specification of non-Markovian rewards in Markov Decision Processes (MDPs) with large state spaces. Our approach leverage…