paper-with-me

홈 › Papers

Characterizing and computing stable models of logic programs: The non-stratified case

2014-02-21 · Gianpaolo Brignoli, Stefania Costantini, Ottavio D'Antona, Alessandro Provetti

Stable Logic Programming (SLP) is an emergent, alternative style of logic programming: each solution to a problem is represented by a stable model of a deductive database/function-free logic program encoding the problem itself. Several implementations now exist for stable logic programming, and their performance is rapidly improving. To make SLP generally applicable, it should be possible to check for consistency (i.e., existence of stable models) of the input program before attempting to answer queries. In the literature, only rather strong sufficient conditions have been proposed for consistency, e.g., stratification. This paper extends these results in several directions. First, the syntactic features of programs, viz. cyclic negative dependencies, affecting the existence of stable models are characterized, and their relevance is discussed. Next, a new graph representation of logic programs, the Extended Dependency Graph (EDG), is introduced, which conveys enough information for reasoning about stable models (while the traditional Dependency Graph does not). Finally, we show that the problem of the existence of stable models can be reformulated in terms of coloring of the EDG.

📄 PDF Abstract BibTeX arXiv:1402.5436

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

How Rules Represent Causal Knowledge: Causal Modeling with Abductive Logic Programs

2025-07-07 · Kilian Rückschloß, Felix Weitkämper arxiv

Pearl observes that causal knowledge enables predicting the effects of interventions, such as actions, whereas descriptive knowledge only permits drawing conclusions from observation. This paper extends Pearl's approach …

The Stable Model Semantics for Higher-Order Logic Programming

2024-08-20 · Bart Bogaerts, Angelos Charalambidis, Giannos Chatziagapis, Babis Kostopoulos 외

We propose a stable model semantics for higher-order logic programs. Our semantics is developed using Approximation Fixpoint Theory (AFT), a powerful formalism that has successfully been used to give meaning to diverse n…

On the Semantics and Complexity of Probabilistic Logic Programs

2017-01-31 · Fabio Gagliardi Cozman, Denis Deratani Mauá

We examine the meaning and the complexity of probabilistic logic programs that consist of a set of rules and a set of independent probabilistic facts (that is, programs based on Sato's distribution semantics). We focus o…

Inductive Learning for Possibilistic Logic Programs Under Stable Models

2025-10-08 · Hongbo Hu, Yisong Wang, Yi Huang, Kewen Wang arxiv

Possibilistic logic programs (poss-programs) under stable models are a major variant of answer set programming (ASP). While its semantics (possibilistic stable models) and properties have been well investigated, the prob…

Weighted Rules under the Stable Model Semantics

2026-05-10 · Joohyung Lee, Yi Wang arxiv

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 semant…