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Multiagent systems, learning in games, and feedback control

Many engineering systems, as well as natural and social systems, can be modeled as a collection of networked components—each subject to local interactions with neighboring elements and each making local adjustments based on local considerations. Such models naturally fit within the framework of “learning in games” or “evolutionary games”, in which multiple decision making agents adaptively adjust their strategies in an effort to optimize local objectives that can be in conflict with each other. Of particular concern is the issue of long term behavior and how agent strategies can converge to a strategic (Nash) equilibrium. This talk will focus on recent advances in adaptive dynamics that can enable strategic convergence even for long standing “counterexamples” through the use of fundamental feedback control concepts. The talk also will present complementary work on coordination in large scale games.

Type of Seminar:
Symposium on Control and Computation
Prof. Jeff Shamma
University of California, Los Angeles
Jun 22, 2005   9:15

ETH-Zentrum, Gloriastrasse 35, Zurich, Room ETZ E8
Contact Person:

Prof. M. Morari
No downloadable files available.
Biographical Sketch:
Jeff S. Shamma is a Professor of Mechanical and Aerospace Engineering at the University of California, Los Angeles (UCLA). Before joining UCLA in 1999, he held faculty positions at the University of Minnesota, Minneapolis, Department of Electrical Engineering, and the University of Texas, Austin, Department of Aerospace Engineering. He received the Ph.D. degree in Systems Science and Engineering in 1988 from the Massachusetts Institute of Technology. He is a recipient of a 1992 NSF Young Investigator Award and the 1996 Donald P. Eckman Award of the American Automatic Control Council, and was a Plenary Speaker at the 1998 American Control Conference.