Wednesday, December 1, 2021 - 1:00pm to 2:00pm

Speaker Information

Noam Brown
Research Scientist
Facebook AI Research


The field of artificial intelligence has had a number of high-profile successes in the domain of perfect-information games like chess and Go where all participants know the exact state of the world. But real-world strategic interactions typically involve hidden information, such as in negotiations, cybersecurity, and financial markets. Past AI techniques fall apart in these settings, with poker serving as the classic benchmark and challenge problem. In this talk I will cover the key breakthroughs behind Libratus and Pluribus, the first AI agents to defeat elite human professionals in two-player no-limit poker and multiplayer no-limit poker, respectively. In particular, I will discuss new equilibrium-finding algorithms and depth-limited search techniques for imperfect-information games that are orders of magnitude faster than prior approaches. Finally, I will conclude with recent work generalizing these results to other imperfect-information multi-agent settings beyond poker.

Speaker Bio

Noam Brown is a Research Scientist at Facebook AI Research working on multi-agent artificial intelligence and computational game theory, with a particular focus on sequential imperfect-information games. He co-created Libratus and Pluribus, the first AIs to defeat top humans in two-player no-limit poker and multiplayer no-limit poker, respectively. He has received the Marvin Minsky Medal for Outstanding Achievements in AI, was named one of MIT Tech Review's 35 Innovators Under 35, and his work on Pluribus was named by Science Magazine to be one of the top 10 scientific breakthroughs of 2019. Noam received his PhD from Carnegie Mellon University, for which he received the IFAAMAS Victor Lesser Distinguished Dissertation Award and the CMU School of Computer Science Distinguished Dissertation Award.