Machine-learning based control of complex multi-agent systems for search and rescue operations in natural disasters (MENTOR)

PRIN 2022 Musolesi

Abstract

The overarching goal of MENTOR is to combine Multi-Agent Reinforcement Learning with control theoretic approaches for the development of new more efficient strategies for the control of autonomous multi-agent systems and explore their application to the problem of designing cooperative agents able to perform challenging search-and-rescue operations in uncertain environments. The project is highly focused on combining control theoretic tools with machine learning. It therefore comprises two Reaserch Units at the University of Naples Federico II and the University of Bologna with complementary expertise and know-how on control techniques, reinforcement learning, mathematical modelling, complex systems, herding and autonomous systems.

Dettagli del progetto

Responsabile scientifico: Mirco Musolesi

Strutture Unibo coinvolte:
Dipartimento di Informatica - Scienza e Ingegneria

Coordinatore:
Università  degli Studi di NAPOLI Federico II(Italy)

Contributo totale Unibo: Euro (EUR) 88.000,00
Durata del progetto in mesi: 29
Data di inizio 28/09/2023
Data di fine: 28/02/2026

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