CS Distinguished Colloquium: Eva Tardos, "Learning & Efficiency of Outcomes in Games"

Friday, April 27, 2018
11:00 a.m.
2117 CSIC
Rebecca Copeland
301 405 6602
rebeccac@umd.edu

Computer Science Department Distinguished Colloquium

Learning & Efficiency of Outcomes in Games: A Talk on Abstract Selfish Behavior

Eva Tardos
Jacob Gould Schurman Professor of Computer Science
Cornell University

Selfish behavior can often lead to suboptimal outcome for all participants, a phenomenon illustrated by many classical examples in game theory. Over the last decade we developed good understanding on how to quantify the impact of strategic user behavior on the overall performance in many games (including traffic routing as well as online auctions). In this talk we will focus on games where players use a form of learning that helps them to adapt to the environment, and consider two closely related questions: What are broad classes of learning behaviors that guarantee high social welfare in games, and are these results robust to situations when game or the population of players is dynamically changing.

 

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