Mathematical Foundations for AI Agents in Complex Environments
Description
A workshop by the American Institute of Mathematics (Sept 28-Oct 2, 2026 in Pasadena) exploring mathematical principles for designing robust, generalizable AI agents in dynamic multi-agent systems.
Highlights
Focus on mathematical foundations of AI agents operating in dynamic, multi-agent environments. Explore robustness, equilibrium analysis, and control theory in interactive systems. Sponsored by AIM and the National Science Foundation (NSF). Organized by Eric Mazumdar and Adam Wierman. Runs in an ‘AIM-style’ format with lectures, discussion groups, working sessions, and open problems suggested by participants. Participants will engage in synthesizing ideas from AI, game theory, behavioral economics, and control theory. Aimed at designing AI agents that generalize beyond training data and perform safely in complex ecosystems. Applications for support and participation are now closed. Held in-person at AIM’s facility at Caltech, Pasadena.
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Cary Lefton
Theme:Pasadena, United States
Emily Valera
Theme:91744
Kayla Partridge
Theme:Student
Schroedter Kinman
Theme:Union
Synthia Chesebro
Theme:Healer
Keith Senior
Theme:Pasadena, United States
Michael Wright
Theme:Movie Extra
joy
Theme:Crystal Healer
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