Learning and Efficiency in Games with Dynamic Population
March 30, 2016, 2:30p, Room 120, New Computer Science Building

Abstract
Selfish behavior can often lead to suboptimal outcome for all participants. This is especially true in dynamically changing environments where the game or the set of the participants can change at any time without the players realizing it. Over the last decade, a good understanding has been developed that quantifies the impact of strategic user behavior on overall performance via studying stable Nash equilibria of the games. In this talk, Tardos will discuss the quality of outcomes in games when the population of players is dynamically changing, and where participants have to adapt to the dynamic environment. This joint work with Thodoris Lykouris and Vasilis Syrgkanis shows that in large classes of games (including congestion games), if players use a form of learning that helps them to adapt to the changing environment, they guarantee high social welfare, even under very frequent changes.

Research, Life, and Career Panel Discussion
4:00p, Room 220, New Computer Science Building

Join preeminent computer scientist and mathematician, Professor Eva Tardos, for a lively discussion on managing your research, meeting your personal life demands, and finding the right career opportunities. Bring your questions and be ready to network with faculty, WiCS members, and researchers. Refreshments will be provided.

Professor Tardos’ Biography
​Eva Tardos is a Jacob Gould Schurman Professor of Computer Science at Cornell University where she was Computer Science department chair from 2006-2010. She received her BA and PhD from Eotvos University in Budapest and joined the Cornell faculty in 1989. She has been elected to the National Academy of Engineering, the National Academy of Sciences, the American Academy of Arts and Sciences, is an external member of the Hungarian Academy of Sciences, and is the recipient of a number of fellowships and awards including the Packard Fellowship, the Goedel Prize, Dantzig Prize, Fulkerson Prize, and the IEEE Technical Achievement Award. Tardos’s research interest is algorithms and algorithmic game theory, the subarea of theoretical computer science theory of designing systems and algorithms for selfish users. Her research focuses on algorithms and games on networks. She is most known for her work on network-flow algorithms, approximation algorithms, and quantifying the efficiency of selfish routing.