An Aggregative Game Framework for the Analysis of Socio-Technical Systems

Francesca PariseDate: March 28, 2019
Location: EE Conference Room (1300 Mudd)
Speaker: Francesca Parise
Faculty host: Prof. Debasis Mitra

Abstract: Many of today’s most promising technological systems involve large numbers of autonomous agents that influence each other and make strategic decisions within a given infrastructure. Examples include demand-response methods in energy markets, opinion dynamics and targeted marketing in social networks, routing decisions in transportation systems or economic exchange and international trade in financial networks. The analysis of agents behavior and equilibrium outcome in these large scale systems necessitates the development of new theoretical and algorithmic tools that combine ideas from game, network and control theory.

In this talk, I discuss how aggregative games can help us achieve such a goal by providing a systematic framework for the modeling and control of large scale socio-technical systems. Specifically, I will touch on three models. First, I will present how “average aggregative games”  can be used to model systems where each agent is affected by the average of the actions of the rest of the population and how iteratively broadcast information can be used to coordinate agents behavior. Second, I will consider systems where agents interactions are heterogeneous and can be described by a network. I will present a variational inequality framework for the analysis of such “network games”  which allows us to extend previous literature results, gain a systematic understanding of how network interactions affect the equilibrium outcome and plan targeted interventions based on agents centrality measures in social and financial networks. Finally, I will focus on a new game theoretical framework that I am developing to model strategic interactions in large scale networks by using the concept of “graphon games” and I will illustrate how this framework can be exploited to design interventions that are robust to stochastic network variations.

Bio: Francesca Parise is a postdoctoral researcher at the Laboratory for Information and Decision Systems at MIT. She defended her PhD at the Automatic Control Laboratory, ETH Zurich, Switzerland in 2016 and she received the B.Sc. and M.Sc. degrees in Information and Automation Engineering in 2010 and 2012, respectively, from the University of Padova, Italy, where she simultaneously attended the Galilean School of Excellence.

Francesca’s main research interest is in control, network and game theory. She has worked on a broad set of topics, including systems biology, reachability analysis, distributed multi-agent systems, network analysis, aggregative games and opinion dynamics.

Francesca was recognized as an EECS rising star in 2017 and is the recipient of the Guglielmo Marin Award from the “Istituto Veneto di Scienze, Lettere ed Arti”, the SNSF Early Postdoc Fellowship, the SNSF Advanced Postdoc Fellowship and the ETH Medal for her doctoral work.

Event Contact: Eliese Lissner |

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