Iterative variable elimination in ASP

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In recent years, a large variety of approaches for forgetting in Answer Set Programming (ASP) have been proposed, in the form of specific operators, or classes of operators, following different principles and obeying different properties. A recent comprehensive overview of existing operators and properties provides a uniform picture of the landscape, including many novel results on relations between properties and operators. In this paper, we introduce four new properties not considered previously and show that these are indeed succinct and relevant additions providing novel results and insights, further strengthening established relations between existing operators. Most notably among these, the invariance to permutations of the order of forgetting a set of atoms iteratively raises interesting questions with surprising results.

Original languageEnglish
Title of host publicationProgress in Artificial Intelligence - 18th EPIA Conference on Artificial Intelligence, EPIA 2017, Proceedings
PublisherSpringer Verlag
Pages643-656
Number of pages14
Volume10423 LNAI
ISBN (Print)9783319653396
DOIs
Publication statusPublished - 2017
Event18th EPIA Conference on Artificial Intelligence, EPIA 2017 - Porto, Portugal
Duration: 5 Sep 20178 Sep 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10423 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th EPIA Conference on Artificial Intelligence, EPIA 2017
CountryPortugal
CityPorto
Period5/09/178/09/17

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  • Cite this

    Knorr, M., Gonçalves, R., & Leite, J. (2017). Iterative variable elimination in ASP. In Progress in Artificial Intelligence - 18th EPIA Conference on Artificial Intelligence, EPIA 2017, Proceedings (Vol. 10423 LNAI, pp. 643-656). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10423 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-65340-2_53