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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…
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…
Affinity-Based Hierarchical Learning of Dependent Concepts for Human Activity Recognition
Aomar Osmani, Massinissa Hamidi, Pegah Alizadeh
In multi-class classification tasks, like human activity recognition, it is often assumed that classes are separable. In real applications, this assumption becomes strong and gener…