Understanding and coordinating cooperation and competition between intelligent decision makers with shared resources is perhaps the most crucial challenge of our connected society
Giuseppe Belgioioso is Doctoral Candidate at the Control Systems (CS) Group at the Department of Electrical Engineering. His research focuses on Game Theory, Operathor Theory and Distributed Optimization for studying and solving coordination, decision and control problems that arise in complex network systems, such as power grids, communication and transportation networks. These complex systems consist of large populations of rational and autonomous agents, and require effective multi-agent coordination and control actions for their safe and efficient operation. While multi-agent optimization is an established methodology for cooperative deciosion makers, a paradigm shift is necessary to ensure safe and efficient operation of large-scale network systems with possibly noncooperative or self-interested agents. With this aim, game theory and operator theory are embraced to design automated computational methods for solving coordination, decision and control problem in modern large-scale network systems.
Giuseppe Belgioioso is currently a Doctoral Candidate in the Control System (CS) Group at Eindhoven University of Technology, The Netherlands. Born in Venice in 1990, he received the Bachelor degree in Information Engineering in September 2012 and the Master degree (cum laude) in Automation Engineering in April 2015, both at the University of Padova, Italy. From Febraury to July 2014 he visited the department of Telecommunication Engineering at the University of Las Palmas the Gran Canaria (ULPGC), Spain. In June 2015 Giuseppe won a research scholarship from the University of Padova and he joined the Automation Engineering Group until April 2016 as a Research Fellow. From Febraury to June 2019 he visited the School of Electrical, Computer and Energy Engineering at Arizona State University (ASU), USA.
A distributed proximal-point algorithm for nash equilibrium seeking in generalized potential games with linearly coupled cost functions18th European Control Conference, ECC 2019 (2019)
An asynchronous, forward-backward, distributed generalized nash equilibrium seeking algorithm18th European Control Conference, ECC 2019 (2019)
A Douglas-Rachford splitting for semi-decentralized equilibrium seeking in generalized aggregative games57th IEEE Conference on Decision and Control, CDC 2018 (2019)
Projected-gradient algorithms for generalized equilibrium seeking in aggregative games arepreconditioned forward-backward methods16th European Control Conference, ECC 2018 (2018)
On the convergence of discrete-time linear systemsIEEE Control Systems Letters (2018)
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