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A Coalgebraic Perspective on Probabilistic Logic Programming

Authors Tao Gu, Fabio Zanasi

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Author Details

Tao Gu
  • University College London, London, UK
Fabio Zanasi
  • University College London, London, UK

Funding

  • Zanasi, Fabio: partial support from epsrc grant n. EP/R020604/1.

Acknowledgements

Fabio Zanasi acknowledges support from epsrc grant n. EP/R020604/1. The authors thank Alessandro Facchini for useful pointers to the literature, and the anonymous reviewers for the useful comments and feedback.

Cite AsGet BibTex

Tao Gu and Fabio Zanasi. A Coalgebraic Perspective on Probabilistic Logic Programming. In 8th Conference on Algebra and Coalgebra in Computer Science (CALCO 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 139, pp. 10:1-10:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/LIPIcs.CALCO.2019.10

Abstract

Probabilistic logic programming is increasingly important in artificial intelligence and related fields as a formalism to reason about uncertainty. It generalises logic programming with the possibility of annotating clauses with probabilities. This paper proposes a coalgebraic perspective on probabilistic logic programming. Programs are modelled as coalgebras for a certain functor F, and two semantics are given in terms of cofree coalgebras. First, the cofree F-coalgebra yields a semantics in terms of derivation trees. Second, by embedding F into another type G, as cofree G-coalgebra we obtain a "possible worlds" interpretation of programs, from which one may recover the usual distribution semantics of probabilistic logic programming.

Subject Classification

ACM Subject Classification
  • Theory of computation
  • Theory of computation → Logic
Keywords
  • probabilistic logic programming
  • coalgebraic semantics
  • distribution semantics

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