2019/05/17 by Sandra Dylus, Dylus, Sandra, Jan Christiansen +3
Computer Science · #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Logic, Reasoning, and Knowledge #Programming Languages (cs.PL) #Semantic Web and Ontologies
paper · pdf · doi:10.48550/arxiv.1905.07212
openalex publication_date 2019/05/17 · openalex created_date 2022/07/29 · openalex updated_date 2026/07/28
This paper presents PFLP, a library for probabilistic programming in the\nfunctional logic programming language Curry. It demonstrates how the concepts\nof a functional logic programming language support the implementation of a\nlibrary for probabilistic programming. In fact, the paradigms of functional\nlogic and probabilistic programming are closely connected. That is, language\ncharacteristics from one area exist in the other and vice versa. For example,\nthe concepts of non-deterministic choice and call-time choice as known from\nfunctional logic programming are related to and coincide with stochastic\nmemoization and probabilistic choice in probabilistic programming,\nrespectively. We will further see that an implementation based on the concepts\nof functional logic programming can have benefits with respect to performance\ncompared to a standard list-based implementation and can even compete with\nfull-blown probabilistic programming languages, which we illustrate by several\nbenchmarks. Under consideration in Theory and Practice of Logic Programming\n(TPLP).\n