Recent years have witnessed significant interest in the area of distributed or networked control systems, with applications ranging from autonomous vehicle teams to communication networks to smart grid energy systems. The setup is a collection of decision-making components with local information and limited communication interacting to balance a collective objective with local incentives. While game theory is well known for its traditional role as a modeling framework in social sciences, it is seeing growing interest as a design approach for distributed control. Of particular interest is game theoretic learning, in which the focus shifts away from equilibrium solution concepts and towards the dynamics of how decision makers reach equilibrium. This talk presents a tutorial overview of game theoretic learning, from its origins as a "descriptive" tool for social systems to its "prescriptive" role as an approach to design on linear learning algorithms for distributed architecture control. The talk presents a sampling of prior and recent results in these areas along with several illustrative examples of distributed coordination.

 

Jeff Shamma is the Julian T. Hightower Chair in Systems & Control in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. Jeff received a BS in Mechanical Engineering from Georgia Tech in 1983 and a PhD in Systems Science and Engineering from the Massachusetts Institute of Technology in 1988. Prior to returning to Georgia Tech in 2007, he held faculty positions at the University of Minnesota, University of Texas-Austin, and University of California-Los Angeles. Jeff is a recipient of the NSF Young Investigator Award (1992) and the American Automatic Control Council Donald P. Eckman Award (1996), and a Fellow of the IEEE (2006). He previously served on the Air Force Scientific Advisory Board (2008--2011) and is currently an Associate Editor for the IEEE Transactions on Cybernetics (2009--present) and Games (2012--present) and a Senior Editor for the newly formed IEEE Transactions on Control of Network Systems. His most recent research has been in the area of game theory and decision making for multiagent models in engineered and societal networked systems.