Learning Equilibria in Simulation-Based Games - Amy Greenwald, Professor, Brown University

Описание к видео Learning Equilibria in Simulation-Based Games - Amy Greenwald, Professor, Brown University

Conference Website: https://saiconference.com/IntelliSys

Abstract: We describe a methodology for the design of parametric mechanisms, which are multiagent systems inhabited by strategic agents, with knobs that can be adjusted to achieve specific goals. For example, a network designer might seek a design that minimizes congestion assuming selfish agents. Our methodology applies under two key conditions: 1. the mechanisms induce games that can be simulated, but that do not afford an analytic description, 2. the agents play approximate equilibria in these simulation-based games. Under these conditions, we use the probably approximately correct learning framework to construct algorithms that learn equilibria. We show eperimentally that our methodology can be used to design effective mechanisms that capture stylized, but rich multiagent systems, such as advertisement exchanges, which are not generally amenable to analytical mechanism design.

About the Speaker: Amy Greenwald is Professor of Computer Science at Brown University in Providence, Rhode Island. Greenwald was also a visiting researcher at the Artificial Intelligence Research Center at the Japanese National Institute of Advanced Industrial Science and Technology in Tokyo in 2018--19; a visiting researcher in the Algorithmic Economics Lab at Microsoft Research in New York City in 2015; and a visiting professor at the Erasmus Research Institute of Management in Rotterdam in 2011. She was named a Fulbright Scholar in 2011 (though she declined the award); she was awarded a Sloan Fellowship in 2006; she was nominated for the 2002 Presidential Early Career Award for Scientists and Engineers (PECASE); and she was named one of the Computing Research Association's Digital Government Fellows in 2001. Before Brown, she worked for a short time as a post-doc at IBM's T.J. Watson Research Center, where her "Shopbots and Pricebots" paper was named Best Paper at IBM Research in 2000. Finally, Greenwald is active in promoting diversity in Computer Science, leading multiple K-12 initiatives in which Brown undergraduates teach computer science to Providence public school students.Amy Greenwald is Professor of Computer Science at Brown University in Providence, Rhode Island. Greenwald was also a visiting researcher at the Artificial Intelligence Research Center at the Japanese National Institute of Advanced Industrial Science and Technology in Tokyo in 2018--19; a visiting researcher in the Algorithmic Economics Lab at Microsoft Research in New York City in 2015; and a visiting professor at the Erasmus Research Institute of Management in Rotterdam in 2011. She was named a Fulbright Scholar in 2011 (though she declined the award); she was awarded a Sloan Fellowship in 2006; she was nominated for the 2002 Presidential Early Career Award for Scientists and Engineers (PECASE); and she was named one of the Computing Research Association's Digital Government Fellows in 2001. Before Brown, she worked for a short time as a post-doc at IBM's T.J. Watson Research Center, where her "Shopbots and Pricebots" paper was named Best Paper at IBM Research in 2000. Finally, Greenwald is active in promoting diversity in Computer Science, leading multiple K-12 initiatives in which Brown undergraduates teach computer science to Providence public school students.

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