The joy of Probabilistic Answer Set Programming: Semantics, complexity, expressivity, inference

Fabio Gagliardi Cozman, Denis Deratani Mauá

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Probabilistic Answer Set Programming (PASP) combines rules, facts, and independent probabilistic facts. We argue that a very useful modeling paradigm is obtained by adopting a particular semantics for PASP, where one associates a credal set with each consistent program. We examine the basic properties of PASP under this credal semantics, in particular presenting novel results on its complexity and its expressivity, and we introduce an inference algorithm to compute (upper) probabilities given a program.

Original languageEnglish
Pages (from-to)218-239
Number of pages22
JournalInternational Journal of Approximate Reasoning
Volume125
DOIs
StatePublished - Oct 2020
Externally publishedYes

Keywords

  • Answer Set Programming
  • Computational complexity
  • Credal sets
  • Descriptive complexity
  • Logic programming
  • Probabilistic programming

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