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Related papers: On the Strong Equivalences of LPMLN Programs

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LPMLN is a powerful knowledge representation and reasoning tool that combines the non-monotonic reasoning ability of Answer Set Programming (ASP) and the probabilistic reasoning ability of Markov Logic Networks (MLN). In this paper, we…

Logic in Computer Science · Computer Science 2023-06-22 Bin Wang , Jun Shen , Shutao Zhang , Zhizheng Zhang

Strong equivalence is a well-studied and important concept in answer set programming (ASP). $\rm LP^{MLN}$ is a probabilistic extension of answer set programs with the weight scheme adapted from Markov Logic. Because of the semantic…

Logic in Computer Science · Computer Science 2019-05-21 Man Luo

LPMLN is a probabilistic extension of answer set programs with the weight scheme adapted from Markov Logic. We study the concept of strong equivalence in LPMLN, which is a useful mathematical tool for simplifying a part of an LPMLN program…

Logic in Computer Science · Computer Science 2019-09-20 Joohyung Lee , Man Luo

LPMLN is a recent addition to probabilistic logic programming languages. Its main idea is to overcome the rigid nature of the stable model semantics by assigning a weight to each rule in a way similar to Markov Logic is defined. We present…

Artificial Intelligence · Computer Science 2017-12-04 Joohyung Lee , Samidh Talsania , Yi Wang

LPMLN is a recently introduced formalism that extends answer set programs by adopting the log-linear weight scheme of Markov Logic. This paper investigates the relationships between LPMLN and two other extensions of answer set programs:…

Artificial Intelligence · Computer Science 2025-06-17 Joohyung Lee , Zhun Yang

In the field of Answer Set Programming (ASP), two logic programs are strongly equivalent if they are ordinarily equivalent under any extensions. This property provides a theoretical foundation for studying many aspects of logic programs…

Logic in Computer Science · Computer Science 2021-12-07 Zhizheng Zhang , Shutao Zhang , Yanghe Feng , Bin Wang

In recent research on non-monotonic logic programming, repeatedly strong equivalence of logic programs P and Q has been considered, which holds if the programs P union R and Q union R have the same answer sets for any other program R. This…

Artificial Intelligence · Computer Science 2007-05-23 Thomas Eiter , Michael Fink , Stefan Woltran

Epistemic Logic Programs (ELPs), that is, Answer Set Programming (ASP) extended with epistemic operators, have received renewed interest in recent years, which led to a flurry of new research, as well as efficient solvers. An important…

Logic in Computer Science · Computer Science 2018-11-13 Wolfgang Faber , Michael Morak , Stefan Woltran

Answer set programming is a prominent declarative programming paradigm used in formulating combinatorial search problems and implementing different knowledge representation formalisms. Frequently, several related and yet substantially…

Artificial Intelligence · Computer Science 2023-03-01 Yuliya Lierler

Logic programs P and Q are strongly equivalent if, given any program R, programs P union R and Q union R are equivalent (that is, have the same answer sets). Strong equivalence is convenient for the study of equivalent transformations of…

Logic in Computer Science · Computer Science 2007-05-23 Hudson Turner

Logic programming under the answer-set semantics nowadays deals with numerous different notions of program equivalence. This is due to the fact that equivalence for substitution (known as strong equivalence) and ordinary equivalence are…

Artificial Intelligence · Computer Science 2007-12-07 Stefan Woltran

Answer Set Programming (ASP) is a powerful paradigm for non-monotonic reasoning. Recently, large language models (LLMs) have demonstrated promising capabilities in logical reasoning. Despite this potential, current evaluations of LLM…

Artificial Intelligence · Computer Science 2025-07-29 Lin Ren , Guohui Xiao , Guilin Qi , Yishuai Geng , Haohan Xue

Strong equivalence between knowledge bases ensures the possibility of replacing one with the other without affecting reasoning outcomes, in any given context. This makes it a crucial property in nonmonotonic formalisms. In particular, the…

Artificial Intelligence · Computer Science 2026-05-15 Giovanni Buraglio , Wolfgang Dvorak , Stefan Woltran

In answer set programming (ASP), a problem at hand is solved by (i) writing a logic program whose answer sets correspond to the solutions of the problem, and by (ii) computing the answer sets of the program using an answer set solver as a…

Artificial Intelligence · Computer Science 2007-05-23 Tomi Janhunen , Emilia Oikarinen

Answer Set Programming (ASP) is a declarative programming paradigm based on logic programming and non-monotonic reasoning. It is a tremendously powerful tool for describing and solving combinatorial problems. Like any other language, ASP…

Artificial Intelligence · Computer Science 2025-11-13 Connar Hite , Sean Saud , Raef Taha , Nayim Rahman , Tanvir Atahary , Scott Douglass , Tarek Taha

LPMLN is a probabilistic extension of answer set programs with the weight scheme derived from that of Markov Logic. Previous work has shown how inference in LPMLN can be achieved. In this paper, we present the concept of weight learning in…

Artificial Intelligence · Computer Science 2018-10-10 Joohyung Lee , Yi Wang

Answer Set Programming (ASP) is a prominent rule-based language for knowledge representation and reasoning with roots in logic programming and non-monotonic reasoning. The aim to capture the essence of removing (ir)relevant details in ASP…

Artificial Intelligence · Computer Science 2023-12-14 Zeynep G. Saribatur , Stefan Woltran

Logic Programs with Ordered Disjunction (LPODs) extend classical logic programs with the capability of expressing preferential disjunctions in the heads of program rules. The initial semantics of LPODs, although simple and quite intuitive,…

Logic in Computer Science · Computer Science 2022-05-11 Angelos Charalambidis , Christos Nomikos , Panos Rondogiannis

While large language models (LLMs), such as GPT-3, appear to be robust and general, their reasoning ability is not at a level to compete with the best models trained for specific natural language reasoning problems. In this study, we…

Computation and Language · Computer Science 2023-07-18 Zhun Yang , Adam Ishay , Joohyung Lee

Epistemic Logic Programs (ELPs) extend Answer Set Programming (ASP) with epistemic negation and have received renewed interest in recent years. This led to the development of new research and efficient solving systems for ELPs. In practice,…

Logic in Computer Science · Computer Science 2020-02-19 Wolfgang Faber , Michael Morak , Stefan Woltran
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