Chun Kai Ling, a doctoral student at Carnegie Mellon University, will deliver a talk as part of CSRAI's Young Achievers Symposium.
"Towards Scalable Game Theoretic Approaches for Addressing Societal Challenges"
Game Theory underpins many exciting breakthroughs, ranging from superhuman performance in video and board games to societal applications such as airport security and wildlife poaching prevention. However, realizing the full potential of game theory requires overcoming two obstacles: (i) reasoning about games where game parameters are not available upfront, and (ii) efficiently solving large general-sum games seen in real-world applications. This talk will discuss three directions to address these challenges. First, Ling will introduce an end-to-end framework based on differentiable optimization which is able to infer unknown game parameters using only samples of player actions in an equilibrium. Second, they will discuss how online subgame resolving, a widely used method in efficient zero-sum game solvers, can be generalized in a principled fashion to various general-sum equilibrium, allowing us to solve games orders of magnitude larger than purely offline methods. Third, they will show how to solve large general-sum games by learning the Enforceable Payoff Frontier (EPF) — a generalization of state value that captures the set of joint future payoffs across players. Ling will show how to learn EPFs using appropriate extensions of Bellman backups, allowing them to solve (in some instances) games too large to traverse while maintaining theoretical performance guarantees.
About the Speaker
Chun Kai Ling is a final-year doctoral candidate at Carnegie Mellon University, where they are co-advised by Professors Zico Kolter and Fei Fang. His research interest is in machine learning for noncooperative games, with a focus on inverse game theory and scalable solvers for large general-sum games. He is the recipient of the 2018 IJCAI distinguished paper award. Prior to starting his Ph.D., he completed his undergraduate studies in the National University of Singapore and worked in DSO National Laboratories.
About the Young Achievers Symposium
The Young Achievers Symposium highlights early career researchers in diverse fields of AI for social impact. The symposium series seeks to focus on emerging research, stimulate discussions, and initiate collaborations that can advance research in artificial intelligence for societal benefit. All events in the series are free and open to the public unless otherwise noted. Penn State students, postdoctoral scholars, and faculty with an interest in socially responsible AI applications are encouraged to attend.