The quest to understand intelligence is one of the great scientific endeavors—on par with quests to understand the origins of life or the foundations of the physical world. Several scientific communities have made significant progress in fields like animal cognition, cognitive science, collective intelligence, and artificial intelligence, as well as the social and behavioral sciences. Yet these communities remain largely disconnected. Now is the time to bring them together with mathematicians to develop the mathematical foundations necessary for transformational advances in understanding natural and artificial intelligences.
This long program seeks to develop those foundations. It will build community and collaboration between participants from the domain sciences and participants from relevant mathematical fields, including dynamical systems, statistical physics, theoretical machine learning, probability and (Bayesian) statistics, information theory, high-dimensional geometry, functional analysis, the theory of programming languages, game theory, and category theory.
Jessica Flack (Santa Fe Institute)
Jacob Foster (University of California, Los Angeles (UCLA))
Tom Griffiths (Princeton University)
Boris Hanin (Princeton University)
Max Kleiman-Weiner (Common Sense Machines)
Orit Peleg (University of Colorado Boulder)
Pat Shafto (Rutgers University)
Josh Tenenbaum (Massachusetts Institute of Technology)