Work

Weighted Rules under the Stable Model Semantics

Year: 2026

Type: preprint

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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2605.09519

Authors: Lee, Joohyung, Wang, Yi

Institution: Arizona State University

Language: English

Topic: Logic, Reasoning, and Knowledge

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, Ministry of Science, ICT and Future Planning, Institute for Information and Communications Technology Promotion

Awards: RI: Small: Knowledge Representation and Reasoning under Uncertainty with Probabilistic Answer Set Programming, G7247313360, RI: Small: Answer Set Programming Modulo Theories

OpenAlex ID: W2540354435

Cites: 21

Cited by: 39

Related to: 20