MCCHE Precision Convergence Webinar Series with Tuomas Sandholm
The State of Representing and Solving Games
By Tuomas Sandholm
Carnegie Mellon University, Pennsylvania
With High-Level Panel of Leaders in Science, Technology, On-the-Ground Action, and Policy
Game-theoretic solution concepts provide meticulous definitions of how rational parties should act. That has enabled humans to think rigorously about strategic interactions, leading to game theory revolutionizing many fields such as economics, political science, and biology. So far, game theory has mainly been used for reasoning by humans. The models have therefore been quite stylized and coarse: small enough for humans to solve in their heads or by paper and pen. The goal has been to draw insights from such models, which humans then judiciously apply to the drastically more complicated real world. The boundaries of game theory have thus been defined by the limits of humans. However, many - arguably most - important game classes lie beyond those boundaries. There is now another, more nascent, use of game theory that goes beyond human intelligence. The game is computationally solved in its full detail - or else in a large, faithful abstraction thereof - as opposed to solving a small, stylized version to obtain insights for humans. Novel approaches, game representations, and algorithms from the last 18 years have enabled game theory to advance significantly beyond its traditional boundaries. I will discuss that state of the art. The talk is based on my presentation at the December 2021 Nobel Symposium: 100 Years of Game Theory, and also includes brand new results.
About the speaker
Tuomas Sandholm is Angel Jordan University Professor of Computer Science at Carnegie Mellon University and a serial entrepreneur. His research focuses on the conver-gence of artificial intelligence, economics, and operations research. He is Co-Director of CMU AI. He is the Founder and Director of the Electronic Marketplaces Laboratory. He has published over 500 peer-reviewed papers, holds 25 patents, and his h-index is 91. In addition to his main appointment in the Computer Science Department, he holds appointments in the Machine Learn-ing Department, Ph.D. Program in Algorithms, Combinatorics, and Optimization (ACO), and CMU/UPitt Joint Ph.D. Program in Computational Biology.
About the series
The Precision Convergence series is launched to catalyze unique synergy between, on the one hand, novel partnerships across sciences, sectors and jurisdictions around targeted domains of real-world solutions, and on the other hand, a next generation convergence of AI with advanced research computing and other data and digital architectures such as PSC’s Bridges-2, and supporting data sharing frameworks such as HuBMAP, informing in a real time as possible the design, deployment and monitoring of solutions for adaptive real-world behaviour and context.
The Precision Convergence Webinar Series is co-hosted by The McGill Centre for the Convergence of Health and Economics (MCCHE) at McGill University and The Pittsburgh Supercomputing Center, a joint computational research centre between Carnegie Mellon University and the University of Pittsburgh.