1 citations · 1 across the 4 of their papers we have counts for
5 papers
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…
Selecting Offline Reinforcement Learning Algorithms for Stochastic Network Control
Nicolas Helson, Pegah Alizadeh, Anastasios Giovanidis
Offline Reinforcement Learning (RL) is a promising approach for next-generation wireless networks, where online exploration is unsafe and large amounts of operational data can be r…
Offline Reinforcement Learning for Mobility Robustness Optimization
Pegah Alizadeh, Anastasios Giovanidis, Pradeepa Ramachandra +2
In this work we revisit the Mobility Robustness Optimisation (MRO) algorithm and study the possibility of learning the optimal Cell Individual Offset tuning using offline Reinforce…
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…