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Documents authored by Lierler, Yuliya

Document
System Description
DOI: 10.4230/OASIcs.ICLP.2018.11
SMT-Based Answer Set Solver CMODELS(DIFF) (System Description)

Authors: Da Shen and Yuliya Lierler

Published in: OASIcs, Volume 64, Technical Communications of the 34th International Conference on Logic Programming (ICLP 2018)

Abstract
Many answer set solvers utilize Satisfiability solvers for search. Satisfiability Modulo Theory solvers extend Satisfiability solvers. This paper presents the CMODELS(DIFF) system that uses Satisfiability Modulo Theory solvers to find answer sets of a logic program. Its theoretical foundation is based on Niemala's characterization of answer sets of a logic program via so called level rankings. The comparative experimental analysis demonstrates that CMODELS(DIFF) is a viable answer set solver.
Cite as

Da Shen and Yuliya Lierler. SMT-Based Answer Set Solver CMODELS(DIFF) (System Description). In Technical Communications of the 34th International Conference on Logic Programming (ICLP 2018). Open Access Series in Informatics (OASIcs), Volume 64, pp. 11:1-11:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{shen_et_al:OASIcs.ICLP.2018.11,
  author =	{Shen, Da and Lierler, Yuliya},
  title =	{{SMT-Based Answer Set Solver CMODELS(DIFF)}},
  booktitle =	{Technical Communications of the 34th International Conference on Logic Programming (ICLP 2018)},
  pages =	{11:1--11:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-090-3},
  ISSN =	{2190-6807},
  year =	{2018},
  volume =	{64},
  editor =	{Dal Palu', Alessandro and Tarau, Paul and Saeedloei, Neda and Fodor, Paul},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICLP.2018.11},
  URN =		{urn:nbn:de:0030-drops-98775},
  doi =		{10.4230/OASIcs.ICLP.2018.11},
  annote =	{Keywords: answer set programming, satisfiability modulo theories, constraint satisfaction processing}
}
Document
System Description
DOI: 10.4230/OASIcs.ICLP.2016.1
SMT-Based Constraint Answer Set Solver EZSMT (System Description)

Authors: Benjamin Susman and Yuliya Lierler

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

Abstract
Constraint answer set programming is a promising research direction that integrates answer set programming with constraint processing. Recently, the formal link between this research area and satisfiability modulo theories (or SMT) was established. This link allows the cross-fertilization between traditionally different solving technologies. The paper presents the system ezsmt, one of the first SMT-based solvers for constraint answer set programming. It also presents the comparative analysis of the performance of ezsmt in relation to its peers including solvers EZCSP, CLINGCON, and MINGO. Experimental results demonstrate that SMT is a viable technology for constraint answer set programming.
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Benjamin Susman and Yuliya Lierler. SMT-Based Constraint Answer Set Solver EZSMT (System Description). In Technical Communications of the 32nd International Conference on Logic Programming (ICLP 2016). Open Access Series in Informatics (OASIcs), Volume 52, pp. 1:1-1:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@InProceedings{susman_et_al:OASIcs.ICLP.2016.1,
  author =	{Susman, Benjamin and Lierler, Yuliya},
  title =	{{SMT-Based Constraint Answer Set Solver EZSMT}},
  booktitle =	{Technical Communications of the 32nd International Conference on Logic Programming (ICLP 2016)},
  pages =	{1:1--1:15},
  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.2016.1},
  URN =		{urn:nbn:de:0030-drops-67321},
  doi =		{10.4230/OASIcs.ICLP.2016.1},
  annote =	{Keywords: constraint answer set programming, constraint satisfaction processing, satisfiability modulo theories}
}
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.2012.164
Surviving Solver Sensitivity: An ASP Practitioner’s Guide

Authors: Bryan Silverthorn, Yuliya Lierler, and Marius Schneider

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

Abstract
Answer set programming (ASP) is a declarative programming formalism that allows a practitioner to specify a problem without describing an algorithm for solving it. In ASP, the tools for processing problem specifications are called answer set solvers. Because specified problems are often NP complete, these systems often require significant computational effort to succeed. Furthermore, they offer different heuristics, expose numerous parameters, and their running time is sensitive to the configuration used. Portfolio solvers and automatic algorithm configuration systems are recent attempts to automate the problem of manual parameter tuning, and to mitigate the burden of identifying the right solver configuration. The approaches taken in portfolio solvers and automatic algorithm configuration systems are orthogonal. This paper evaluates these approaches, separately and jointly, in the context of real-world ASP application development. It outlines strategies for their use in such settings, identifies their respective strengths and weaknesses, and advocates for a methodology that would make them an integral part of developing ASP applications.
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Bryan Silverthorn, Yuliya Lierler, and Marius Schneider. Surviving Solver Sensitivity: An ASP Practitioner’s Guide. In Technical Communications of the 28th International Conference on Logic Programming (ICLP'12). Leibniz International Proceedings in Informatics (LIPIcs), Volume 17, pp. 164-175, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@InProceedings{silverthorn_et_al:LIPIcs.ICLP.2012.164,
  author =	{Silverthorn, Bryan and Lierler, Yuliya and Schneider, Marius},
  title =	{{Surviving Solver Sensitivity: An ASP Practitioner’s Guide}},
  booktitle =	{Technical Communications of the 28th International Conference on Logic Programming (ICLP'12)},
  pages =	{164--175},
  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.2012.164},
  URN =		{urn:nbn:de:0030-drops-36192},
  doi =		{10.4230/LIPIcs.ICLP.2012.164},
  annote =	{Keywords: algorithm configuration, algorithm selection, portfolio solving, answer set programming, algorithm portfolios}
}
Document
DOI: 10.4230/LIPIcs.ICLP.2012.277
A Tarskian Informal Semantics for Answer Set Programming

Authors: Marc Denecker, Yuliya Lierler, Miroslaw Truszczynski, and Joost Vennekens

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

Abstract
In their seminal papers on stable model semantics, Gelfond and Lifschitz introduced ASP by casting programs as epistemic theories, in which rules represent statements about the knowledge of a rational agent. To the best of our knowledge, theirs is still the only published systematic account of the intuitive meaning of rules and programs under the stable semantics. In current ASP practice, however, we find numerous applications in which rational agents no longer seem to play any role. Therefore, we propose here an alternative explanation of the intuitive meaning of ASP programs, in which they are not viewed as statements about an agent's beliefs, but as objective statements about the world. We argue that this view is more natural for a large part of current ASP practice, in particular the so-called Generate-Define-Test programs.
Cite as

Marc Denecker, Yuliya Lierler, Miroslaw Truszczynski, and Joost Vennekens. A Tarskian Informal Semantics for Answer Set Programming. In Technical Communications of the 28th International Conference on Logic Programming (ICLP'12). Leibniz International Proceedings in Informatics (LIPIcs), Volume 17, pp. 277-289, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@InProceedings{denecker_et_al:LIPIcs.ICLP.2012.277,
  author =	{Denecker, Marc and Lierler, Yuliya and Truszczynski, Miroslaw and Vennekens, Joost},
  title =	{{A Tarskian Informal Semantics for Answer Set Programming}},
  booktitle =	{Technical Communications of the 28th International Conference on Logic Programming (ICLP'12)},
  pages =	{277--289},
  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.2012.277},
  URN =		{urn:nbn:de:0030-drops-36295},
  doi =		{10.4230/LIPIcs.ICLP.2012.277},
  annote =	{Keywords: Answer set programming, informal semantics, generate-define-test}
}
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