AI for Imperfect-Information Game Settings

Abstract: The field of artificial intelligence has had a number of high-profile successes in the domain of perfect-information games. But real-world strategic interactions are not like chess or Go where all participants know the exact state of the world. Instead, they typically involve hidden information, such as in negotiations, cybersecurity attacks, and financial markets. Techniques used in perfect-information games fall apart when applied to such imperfect-information games, with poker serving as the classic example. Libratus is an AI that, in a 120,000-hand competition, decisively defeated four top professionals in heads-up no-limit Texas hold’em poker, the leading benchmark for imperfect-information games and a long-standing challenge problem for AI in general. In this talk I will explain why past techniques intended for perfect-information multi-agent and imperfect-information single-agent settings break down both in theory and in practice in imperfect-information multi-agent settings, and the advances in Libratus and my later work that overcome those challenges. In particular, I will describe new general methods I developed for state-of-the-art equilibrium finding and real-time planning in imperfect-information games. These techniques all have theoretical guarantees in addition to strong empirical performance, and are domain-independent. I will conclude by discussing applications of this work and future research directions in the area of multi-agent artificial intelligence. Host: Tommi Jaakkola.

Bio: Noam Brown is a PhD candidate in computer science at Carnegie Mellon University advised by Tuomas Sandholm and a Research Scientist at Facebook AI Research. His research combines computational game theory and machine learning to develop AI systems capable of strategic reasoning in large imperfect-information multi-agent settings. He has applied this research to creating Libratus, the first AI to defeat top humans in no-limit poker, which was one of 12 finalists for Science Magazine's Scientific Breakthrough of the Year. Noam received a NeurIPS Best Paper award in 2017, the 2017 Allen Newell Award for Research Excellence, an Outstanding Paper Honorable Mention at AAAI 2019, and the 2019 Marvin Minsky Medal for Outstanding Achievements in AI. His PhD was supported by an Open Philanthropy Project AI fellowship and a Tencent AI Lab fellowship.