CSE Distinguished Lecture
Learning and Efficiency in Games
The fifth speaker in the Fall 2016 CSE Distinguished Lecture Series is Eva Tardos, the Jacob Gould Schurman Professor of Computer Science at Cornell University. Her lecture will focus on “Learning and Efficiency in Games.”
Date: Monday, October 31
Time: 11:00am – Noon
Location: Room 1202, CSE Building
Host: CSE Prof. Shachar Lovett
Abstract: Selfish behavior can often lead to suboptimal outcome for all participants. Over the last decade we have developed good understanding how to quantify the impact of strategic user behavior on overall performance via studying stable Nash equilibria of the games. In this talk we will consider the quality of outcomes when players use a form of learning that helps them to adapt to the environment, will discuss the speed at which learning dynamic approaches the Nash equilibrium welfare. We will also consider games with dynamically changing populations, where participants have to adapt to the dynamic environment. We show that in large classes of games, learning players ensure outcome with high social welfare, even under very frequent changes.
Bio: Eva Tardos is a Jacob Gould Schurman Professor of Computer Science at Cornell University, was Computer Science department chair 2006-2010. She received her BA and PhD from Eotvos University in Budapest. She joined the faculty at Cornell in 1989. She has been elected to the National Academy of Engineering, the National Academy of Sciences, the American Academy of Arts and Sciences, and is an external member of the Hungarian Academy of Sciences. She 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. She is editor editor-in- Chief of the Journal of the ACM, and was editor in the past of several other journals including the SIAM Journal of Computing, and Combinatorica, served as problem committee member for many conferences, and was program committee chair for SODA’96, FOCS’05, and EC’13. Tardos’s research interests include 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.