Weighted Rules under the Stable Model Semantics

arXiv (Cornell University) 2026 Preprint Open access

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Authors: Joohyung Lee, Wang Yi
DOI: 10.48550/arxiv.2605.09519
Cited by: 44
References: 21

Abstract

We introduce the concept of weighted rules under the stable model semantics following the log-linear models of Markov Logic. This provides versatile methods to overcome the deterministic nature of the stable model semantics, such as resolving inconsistencies in answer set programs, ranking stable models, associating probability to stable models, and applying statistical inference to computing weighted stable models. We also present formal comparisons with related formalisms, such as answer set programs, Markov Logic, ProbLog, and P-log.

Fields of Study & Subjects

Logic Reasoning and Knowledge Semantic Web and Ontologies Multi-Agent Systems and Negotiation

Publication details

Journal / source
arXiv (Cornell University)
Pages
145–154
Publication date
10 May 2026
Language
EN
Document type
Preprint