5 citations · 7 across the 7 of their papers we have counts for
4 papers · 1 filter
A Fairness-Oriented Multi-Objective Reinforcement Learning approach for Autonomous Intersection Management
Matteo Cederle, Marco Fabris, Gian Antonio Susto
This study introduces a novel multi-objective reinforcement learning (MORL) approach for autonomous intersection management, aiming to balance traffic efficiency and environmental…
VoI-aware Scheduling Schemes for Multi-Agent Formation Control
Federico Chiariotti, Marco Fabris
Formation control allows agents to maintain geometric patterns using local information, but most existing methods assume ideal communication. This paper introduces a goal-oriented…
Towards Scalable IoT Deployment for Visual Anomaly Detection via Efficient Compression
Arianna Stropeni, Francesco Borsatti, Manuel Barusco +3
Visual Anomaly Detection (VAD) is a key task in industrial settings, where minimizing operational costs is essential. Deploying deep learning models within Internet of Things (IoT)…
Regulating Spatial Fairness in a Tripartite Micromobility Sharing System via Reinforcement Learning
Matteo Cederle, Marco Fabris, Gian Antonio Susto
In the growing field of Shared Micromobility Systems, which holds great potential for shaping urban transportation, fairness-oriented approaches remain largely unexplored. This wor…