<div class="csl-bib-body">
<div class="csl-entry">Beiser, A., Gebser, M., Hecher, M., & Woltran, S. (2025). FastFound: Easing the ASP Bottleneck via Predicate-Decoupled Grounding. In M. Ortiz, R. Wassermann, & T. Schaub (Eds.), <i>Proceedings of the TwentySecond International Conference on Principles of Knowledge Representation and Reasoning</i> (pp. 100–109). IJCAI Organization. https://doi.org/10.24963/kr.2025/10</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/223179
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dc.description.abstract
The grounding bottleneck in Answer Set Programming prohibits large instances from being solved. This is caused by a combinatorial explosion in the grounding phase of standard ground&solve systems. A promising alternative is Body-Decoupled Grounding (BDG), which grounds each body
predicate on its own. However, BDG faces challenges in terms of worst-case grounding size and limited interoperability with other systems.
This paper addresses shortcomings of BDG by introducing FastFound: an alternative foundedness check that significantly reduces grounding sizes, by grounding each predicate on its own. FastFound’s foundedness check is done implicitly, which leads to a quadratic reduction in grounding size. We start by introducing FastFound for tight normal rules, where we observe that this cannot be substantially improved. Then we extend FastFound to head-cycle-free programs and give novel interoperability
results for full disjunctive programs. An experimental evaluation on our prototype shows promising results, as we solve more grounding-heavy tasks than both standard ground&solve systems and BDG.
en
dc.language.iso
en
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dc.subject
Answer Set Programming
en
dc.subject
Logic Programming
en
dc.subject
Grounding Bottleneck
en
dc.subject
Alternative Grounding
en
dc.subject
Quadratic Improvements
en
dc.subject
Grounding Via Solving
en
dc.title
FastFound: Easing the ASP Bottleneck via Predicate-Decoupled Grounding
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.contributor.affiliation
University of Klagenfurt, Austria
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dc.contributor.editoraffiliation
Departamento de Ciência da Computação - Universidade de São Paulo Instituto de Matemática e Estatística (Sao Paulo, BR)
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dc.relation.isbn
978-1-956792-08-9
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dc.relation.issn
2334-1033
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dc.description.startpage
100
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dc.description.endpage
109
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
Proceedings of the TwentySecond International Conference on Principles of Knowledge Representation and Reasoning
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tuw.peerreviewed
true
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tuw.relation.publisher
IJCAI Organization
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tuw.researchTopic.id
I1
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tuw.researchTopic.name
Logic and Computation
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tuw.researchTopic.value
100
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tuw.publication.orgunit
E192-02 - Forschungsbereich Databases and Artificial Intelligence
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tuw.publication.orgunit
E056-13 - Fachbereich LogiCS
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tuw.publication.orgunit
E056-23 - Fachbereich Innovative Combinations and Applications of AI and ML (iCAIML)
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tuw.publisher.doi
10.24963/kr.2025/10
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dc.description.numberOfPages
10
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tuw.author.orcid
0000-0003-0131-6771
-
tuw.author.orcid
0000-0003-1594-8972
-
tuw.editor.orcid
0000-0002-2344-9658
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tuw.editor.orcid
0000-0001-8065-1433
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tuw.event.name
22nd International Conference on Principles of Knowledge Representation and Reasoning (KR25)
en
tuw.event.startdate
11-11-2025
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tuw.event.enddate
17-11-2025
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tuw.event.online
On Site
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tuw.event.type
Event for scientific audience
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tuw.event.place
Melbourne
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tuw.event.country
AU
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tuw.event.presenter
Beiser, Alexander
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wb.sciencebranch
Informatik
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wb.sciencebranch
Mathematik
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.oefos
1010
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wb.sciencebranch.value
80
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wb.sciencebranch.value
20
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item.grantfulltext
none
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item.languageiso639-1
en
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item.cerifentitytype
Publications
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item.openairecristype
http://purl.org/coar/resource_type/c_5794
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item.fulltext
no Fulltext
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item.openairetype
conference paper
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crisitem.author.dept
E192-02 - Forschungsbereich Databases and Artificial Intelligence
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crisitem.author.dept
University of Klagenfurt, Austria
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crisitem.author.dept
E192-02 - Forschungsbereich Databases and Artificial Intelligence
-
crisitem.author.dept
E192-02 - Forschungsbereich Databases and Artificial Intelligence