Wednesday 21 June 2023 at 10:00 AM EDT, 4:00 PM CET

By Lacra Pavel (University of Toronto, Canada)

Register now using the link below:

https://attendee.gotowebinar.com/register/4016850658546866009


Abstract:

Networks are ubiquitous around us. Consider the Internet, with its underlying communication, the smart grid/power network, a network of robots engaged in search and rescue, or a group of people interacting over Facebook. These are all instances of networks of multiple entities/agents that have decision-making capabilities and individual goals, while interacting in a strategic manner. In this talk, we consider decision-making over networks under the umbrella of game theory. In the classical setting of Nash’s game theory each player is assumed to interact with all others and to have complete information. The presence of the network brings in several new issues: complexity of agents’ networked interaction, local/partial information, delayed/asynchronous communication, the curse of dimensionality. In this talk we review some of our group’s work towards addressing these problems.

Presenter’s bio:

Lacra Pavel is a Professor in the Systems Control group, Department of Electrical and Computer Engineering, University of Toronto. She received the Diploma of Engineer in Automatic Control from Technical University Iasi, Romania and the Ph.D. degree in Electrical Engineering from Queen’s University, Canada. She joined University of Toronto in 2002, after a postdoctoral stage at the National Research Council and four years of working in the communication industry. Her research interests are in game theory and distributed optimization in networks, with emphasis on dynamics, system theoretic and control methods. She is the author of the book Game Theory for Control of Optical Networks (Birkhauser-Springer Science). She is a Senior Editor for the IEEE Transactions on Control of Network Systems, a Senior Editor for the IEEE Open Journal of Control Systems and an Associate Editor for the IEEE Transactions on Automatic Control.