Bayesian Network Games
Oct 23, 2013
from 01:00 PM to 02:00 PM
|Where||Engr. IV Bldg., Faraday Room 67-124|
|Contact Name||Prof. Mihaela van der Schaar|
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Prof. Alejandro Ribeiro
University of Pennsylvania
In many situations agents in a network want to take actions corresponding to a joint global operating point while only being able to coordinate and access information in their local neighborhoods. A natural alternative is to let agents select an action that maximizes their expected utility with respect to the information available and a model on the actions they expect will be taken by other agents. We call this action model a Bayesian network game in which agents cooperate with each other while hedging their actions with respect to uncertainty that is inherent in a networked setting. We consider repeated games in which beliefs on the actions of other agents are refined through subsequent observations of neighboring actions. We discuss asymptotic properties of these games and for the particular case of quadratic payoffs we introduce the Quadratic Network Game filter that agents can run locally to update their beliefs, select corresponding optimal actions, and eventually learn a sufficient statistic of the network’s state. Open research directions are discussed to close the talk.
Alejandro Ribeiro received the B.Sc. degree in electrical engineering from the Universidad de la Republica Oriental del Uruguay, Montevideo, in 1998 and the M.Sc. and Ph.D. degree in electrical engineering from the Department of Electrical and Computer Engineering, the University of Minnesota, Minneapolis in 2005 and 2007. From 1998 to 2003, he was a member of the technical staff at Bellsouth Montevideo. After his M.Sc. and Ph.D studies, in 2008 he joined the University of Pennsylvania (Penn), Philadelphia, where he is currently an Assistant Professor at the Department of Electrical and Systems Engineering. His research interests are in the applications of statistical signal processing to the study of networks and networked phenomena. His current research focuses on wireless networks, network optimization, learning in networks, networked control, robot teams, and structured representations of networked data structures. Dr. Ribeiro received the 2012 S. Reid Warren, Jr. Award presented by Penn’s undergraduate student body for outstanding teaching and the NSF CAREER Award in 2010. He is also a Fulbright scholar and the recipient of student paper awards at the 2013 American Control Conference (as adviser), as well as the 2005 and 2006 International Conferences on Acoustics, Speech and Signal Processing.