2 papers
cs.LG2026
Meta-RL with Shared Representations Enables Fast Adaptation in Energy Systems
Théo Zangato, Aomar Osmani, Pegah Alizadeh
Meta-Reinforcement Learning addresses the critical limitations of conventional Reinforcement Learning in multi-task and non-stationary environments by enabling fast policy adaptati…
cs.LG2025
Data-Driven Policy Mapping for Safe RL-based Energy Management Systems
Theo Zangato, Aomar Osmani, Pegah Alizadeh
Increasing global energy demand and renewable integration complexity have placed buildings at the center of sustainable energy management. We present a three-step reinforcement lea…