Report on the probabilistic language scheme

Abstract

Reasoning with probabilistic models is a widespread and successful technique in areas ranging from computer vision, to natural language processing, to bioinformatics. Currently, these reasoning systems are either coded from scratch in general-purpose languages or use formalisms such as Bayesian networks that have limited expressive power. In both cases, the resulting systems are difficult to modify, maintain, compose, and interoperate with. This work presents Probabilistic Scheme, an embedding of probabilistic computation into Scheme. This gives programmers an expressive language for implementing modular probabilistic models that integrate naturally with the rest of Scheme.