most citedOptimizing Energy Management of Smart Grid using Reinforcement Learning aided by Surrogate models built using Physics-informed Neural Networks

10 citations · 10 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2026

Learning in Markov Decision Processes with Exogenous Dynamics

Davide Maran, Davide Salaorni, Marcello Restelli

Reinforcement learning algorithms are typically designed for generic Markov Decision Processes (MDPs), where any state-action pair can lead to an arbitrary transition distribution.…

cs.LG2025★ 10 cited

Optimizing Energy Management of Smart Grid using Reinforcement Learning aided by Surrogate models built using Physics-informed Neural Networks

Julen Cestero, Carmine Delle Femine, Kenji S. Muro +2

Optimizing the energy management within a smart grids scenario presents significant challenges, primarily due to the complexity of real-world systems and the intricate interactions…