Unifying logic and probability: The BLOG language

Abstract:

Logic and probability are ancient subjects whose unification holds significant potential for the field of artificial intelligence. The BLOG (Bayesian LOGic) language provides a way to write probability models using syntactic and semantic devices from first-order logic. In modern parlance, it is a relational, open-universe probabilistic programming language that allows one to define probability distributions over the entire space of first-order model structures that can be constructed given the constant, function, and predicate symbols of the program. I will describe the language mainly through examples and cover its application to monitoring the Comprehensive Nuclear-Test-Ban Treaty.

Stuart Russell is Professor of Computer Science and Smith-Zadeh Professor in Engineering, University of California, Berkeley
Adjunct Professor of Neurological Surgery, University of California, San Francisco.  Stuart Russell is interested in building systems that can act intelligently in the real world. To this end, he works (with various students, postdocs, and collaborators) on a broad spectrum of topics in AI.