AGI 2011 - Probabilistic Programs: A New Language for AI

The Fourth Conference on Artificial General Intelligence Mountain View, California, USA August 3-6, 2011 Probabilistic Programs: A New Language for AI Presented by Noah Goodman, Stanford University ABSTRACT How can logical and probabilistic approaches to understanding intelligence be reconciled? I will argue that probabilistic programming is the best way to merge logic and probability, providing a new set of tools for thinking about representation and inference in systems with human-like intelligence. I will illustrate these ideas by introducing the probabilistic programming language Church (a stochastic LISP), describing two universal inference algorithms (i.e. algorithms that can perform probabilistic inference for any Church program), and giving a series of examples. These examples, drawn from cognitive science and AI, will include multi-agent reasoning and concept learning. About Noah Goodman: http://stanford.edu/~ngoodman/