When you must forget: Beyond strong persistence when forgetting in answer set programming

DOI10.1017/S1471068417000382zbMath1422.68022arXiv1707.05152WikidataQ62046413 ScholiaQ62046413MaRDI QIDQ4592710

João Leite, Matthias Knorr, Stefan Woltran, Ricardo Gonçalves

Publication date: 8 November 2017

Published in: Theory and Practice of Logic Programming (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1707.05152

zbMATH Keywords

computational complexityforgettinganswer set programmingstrong equivalencerelativized equivalence

Mathematics Subject Classification ID

Analysis of algorithms and problem complexity (68Q25) Logic programming (68N17)

Related Items (4)

A Syntactic Operator for Forgetting that Satisfies Strong Persistence ⋮ On the limits of forgetting in answer set programming ⋮ Omission-Based Abstraction for Answer Set Programs ⋮ On syntactic forgetting under uniform equivalence

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Forgetting for knowledge bases in DL-lite
• Logic-based ontology comparison and module extraction, with an application to DL-Lite
• Lazy narrowing: strong completeness and eager variable elimination
• Reasoning under inconsistency: a forgetting-based approach
• How to progress a database
• On the computational cost of disjunctive logic programming: Propositional case
• Nested expressions in logic programs
• Model-theoretic inseparability and modularity of description logic ontologies
• Semantic forgetting in answer set programming
• A bird's-eye view of forgetting in answer-set programming
• Solving logic program conflict through strong and weak forgettings
• Forgetting in ASP: The Forgotten Properties
• Forgetting under the Well-Founded Semantics
• The Logical Difference for the Lightweight Description Logic EL
• The rise and fall of semantic rule updates based onSE-models
• Preserving Strong Equivalence while Forgetting
• A Model-Theoretic Approach to Belief Change in Answer Set Programming
• Dynamic updates of non-monotonic knowledge bases
• You Can't Always Forget What You Want: On the Limits of Forgetting in Answer Set Programming
• An abductive framework for computing knowledge base updates
• A system of interaction and structure
• Knowledge Forgetting in Answer Set Programming
• Forgetting Literals with Varying Propositional Symbols
• Strongly equivalent logic programs

This page was built for publication: When you must forget: Beyond strong persistence when forgetting in answer set programming