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Documents authored by De Cat, Broes

Document
DOI: 10.4230/OASIcs.ICLP.2016.12
Constraint CNF: SAT and CSP Language Under One Roof

Authors: Broes De Cat and Yuliya Lierler

Published in: OASIcs, Volume 52, Technical Communications of the 32nd International Conference on Logic Programming (ICLP 2016)

Abstract
A new language, called constraint CNF, is proposed. It integrates propositional logic with constraints stemming from constraint programming. A family of algorithms is designed to solve problems expressed in constraint CNF. These algorithms build on techniques from both propositional satisfiability and constraint programming. The result is a uniform language and an algorithmic framework, which allow us to gain a deeper understanding of the relation between the solving techniques used in propositional satisfiability and in constraint programming and apply them together.
Cite as

Broes De Cat and Yuliya Lierler. Constraint CNF: SAT and CSP Language Under One Roof. In Technical Communications of the 32nd International Conference on Logic Programming (ICLP 2016). Open Access Series in Informatics (OASIcs), Volume 52, pp. 12:1-12:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@InProceedings{decat_et_al:OASIcs.ICLP.2016.12,
  author =	{De Cat, Broes and Lierler, Yuliya},
  title =	{{Constraint CNF: SAT and CSP Language Under One Roof}},
  booktitle =	{Technical Communications of the 32nd International Conference on Logic Programming (ICLP 2016)},
  pages =	{12:1--12:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-007-1},
  ISSN =	{2190-6807},
  year =	{2016},
  volume =	{52},
  editor =	{Carro, Manuel and King, Andy and Saeedloei, Neda and De Vos, Marina},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICLP.2016.12},
  URN =		{urn:nbn:de:0030-drops-67425},
  doi =		{10.4230/OASIcs.ICLP.2016.12},
  annote =	{Keywords: Propositional Satisfiability, Constraint Programming}
}
Document
DOI: 10.4230/LIPIcs.ICLP.2012.14
Modeling Machine Learning and Data Mining Problems with FO(·)

Authors: Hendrik Blockeel, Bart Bogaerts, Maurice Bruynooghe, Broes De Cat, Stef De Pooter, Marc Denecker, Anthony Labarre, Jan Ramon, and Sicco Verwer

Published in: LIPIcs, Volume 17, Technical Communications of the 28th International Conference on Logic Programming (ICLP'12) (2012)

Abstract
This paper reports on the use of the FO(·) language and the IDP framework for modeling and solving some machine learning and data mining tasks. The core component of a model in the IDP framework is an FO(·) theory consisting of formulas in first order logic and definitions; the latter are basically logic programs where clause bodies can have arbitrary first order formulas. Hence, it is a small step for a well-versed computer scientist to start modeling. We describe some models resulting from the collaboration between IDP experts and domain experts solving machine learning and data mining tasks. A first task is in the domain of stemmatology, a domain of philology concerned with the relationship between surviving variant versions of text. A second task is about a somewhat similar problem within biology where phylogenetic trees are used to represent the evolution of species. A third and final task is about learning a minimal automaton consistent with a given set of strings. For each task, we introduce the problem, present the IDP code and report on some experiments.
Cite as

Hendrik Blockeel, Bart Bogaerts, Maurice Bruynooghe, Broes De Cat, Stef De Pooter, Marc Denecker, Anthony Labarre, Jan Ramon, and Sicco Verwer. Modeling Machine Learning and Data Mining Problems with FO(·). In Technical Communications of the 28th International Conference on Logic Programming (ICLP'12). Leibniz International Proceedings in Informatics (LIPIcs), Volume 17, pp. 14-25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@InProceedings{blockeel_et_al:LIPIcs.ICLP.2012.14,
  author =	{Blockeel, Hendrik and Bogaerts, Bart and Bruynooghe, Maurice and De Cat, Broes and De Pooter, Stef and Denecker, Marc and Labarre, Anthony and Ramon, Jan and Verwer, Sicco},
  title =	{{Modeling Machine Learning and Data Mining Problems with FO(·)}},
  booktitle =	{Technical Communications of the 28th International Conference on Logic Programming (ICLP'12)},
  pages =	{14--25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-43-9},
  ISSN =	{1868-8969},
  year =	{2012},
  volume =	{17},
  editor =	{Dovier, Agostino and Santos Costa, V{\'\i}tor},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICLP.2012.14},
  URN =		{urn:nbn:de:0030-drops-36049},
  doi =		{10.4230/LIPIcs.ICLP.2012.14},
  annote =	{Keywords: Knowledge representation and reasoning, declarative modeling, logic programming, knowledge base systems, FO(·), IDP framework, stemmatology, phylogene}
}
Document
DOI: 10.4230/LIPIcs.ICLP.2012.201
Lazy Model Expansion by Incremental Grounding

Authors: Broes De Cat, Marc Denecker, and Peter Stuckey

Published in: LIPIcs, Volume 17, Technical Communications of the 28th International Conference on Logic Programming (ICLP'12) (2012)

Abstract
Ground-and-solve methods used in state-of-the-art Answer Set Programming and model expansion systems proceed by rewriting the problem specification into a ground format and afterwards applying search. A disadvantage of such approaches is that the rewriting step blows up the original specification for large input domains and is unfeasible in case of infinite domains. In this paper we describe a lazy approach to model expansion in the context of first-order logic that can cope with large and infinite problem domains. The method interleaves grounding and search, incrementally extending the current partial grounding only when necessary. It often allows to solve the original problem without creating the full grounding and is hence more widely applicable than ground-and-solve. We report on an existing implementation within the IDP system and on experiments that show the promise of the method.
Cite as

Broes De Cat, Marc Denecker, and Peter Stuckey. Lazy Model Expansion by Incremental Grounding. In Technical Communications of the 28th International Conference on Logic Programming (ICLP'12). Leibniz International Proceedings in Informatics (LIPIcs), Volume 17, pp. 201-211, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@InProceedings{decat_et_al:LIPIcs.ICLP.2012.201,
  author =	{De Cat, Broes and Denecker, Marc and Stuckey, Peter},
  title =	{{Lazy Model Expansion by Incremental Grounding}},
  booktitle =	{Technical Communications of the 28th International Conference on Logic Programming (ICLP'12)},
  pages =	{201--211},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-43-9},
  ISSN =	{1868-8969},
  year =	{2012},
  volume =	{17},
  editor =	{Dovier, Agostino and Santos Costa, V{\'\i}tor},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICLP.2012.201},
  URN =		{urn:nbn:de:0030-drops-36222},
  doi =		{10.4230/LIPIcs.ICLP.2012.201},
  annote =	{Keywords: Knowledge representation and reasoning, model generation, grounding, IDP framework, first-order logic}
}
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