Game Theory has been a staple of economics research since 1950, when John Nash who is the subject of the movie A Beautiful Mind, published the seminal paper that would win him the Nobel Prize in economics. As game theory has matured, it’s become even more central to the field of economics and social sciences. Recently game theory has been drawing attention in computer science and engineering. Researchers are using it to analyze problems such as optimizing traffic flow, designing smarter cities or preventing blackouts. One of the influences of computer science in game theory is through complexity theory. Thanks to complexity techniques, we know that checking stability of equilibria is NP-hard. Another interesting game-theoretic problem that originated in computer science, but is of interest to the game theory community, is the computation of the so-called "price of anarchy", that is, the cost of using decentralizing solution to a problem (the efficiency loss). In the last decade, both communities have been developing algorithms and learning- in-games tools for computing or designing equilibria. Distributed strategic learning and algorithmic game theory are now keys research areas in these directions. At the same time, the engineering community is applying Game Theory to design and manage new protocols. It is for example used in the Physical layer (together with strategic information theory), MAC layer (coordination in carrier sensing multiple access), Network Layer (optimal selection, placement, congestion, routing, Quality of Service), Transport layer (long-term management of Transmission Control Protocols) and Application layer (Quality of Experience). These recent applications helped the game theory community to formulate novel game theoretic interactions such as Network games, Games-within-Games and multi-layer-multi-resolution-games which were absent in the literature. In this talk we will overview some of these recent interdisciplinary cross-interactions between game theory, computer science and engineering.
Biography Dr. Hamidou Tembine graduated with highest honors in applied mathematics from Ecole Polytechnique (Palaiseau, France) in 2006 and received his Ph.D. degree (with highest honors) in Computer Science from INRIA and University of Avignon (2009). He further received his Master degree in game theory and economics. From 2010 to 2013, he was an associate professor at Ecole Superieure d’Electricite. Currently he is a senior research scientist at KAUST SRI Center for Uncertainty Quantification, CEMSE division. His main research interests are evolutionary games, mean field stochastic games, distributed strategic learning and their applications. He was the recipient of 5 best paper awards in the applications of game theory (ACM Valuetools 2007, IFIP Networking 2008, IEEE/ACM WiOpt 2009, IEEE INFOCOM Workshop 2011, IEEE GHTC 2012). Dr. Tembine is a prolific researcher and holds over 130 scientific publications including journals and conferences. He is author of the book on “distributed strategic learning for engineers “ (published at CRC Press, Taylor & Francis 2012), and co-author of the book “Game Theory and Learning in Wireless Networks” (Elsevier Academic Press). Dr. Tembine has been co-organizer of several meetings on game theory in networking and wireless communications (CDC, ACC, GameSec, ECC, Allerton, NetGCoop, WiOpt, GameNets, Gamecomm). He has been TPC member and reviewer for several international journals and conferences. He has been a visiting researcher at University of California at Berkeley (US), University of McGill (Montreal, Quebec, Canada), University of Illinois at Urbana-Champaign (UIUC, US), Ecole Polytechnique Federale de Lausanne (EPFL, Switzerland) and University of Wisconsin (Madison, US). More details at http://tembine.com/