@article{JanhunenKaminskiOstrowskietal.2017, author = {Janhunen, Tomi and Kaminski, Roland and Ostrowski, Max and Schellhorn, Sebastian and Wanko, Philipp and Schaub, Torsten H.}, title = {Clingo goes linear constraints over reals and integers}, series = {Theory and practice of logic programming}, volume = {17}, journal = {Theory and practice of logic programming}, publisher = {Cambridge Univ. Press}, address = {New York}, issn = {1471-0684}, doi = {10.1017/S1471068417000242}, pages = {872 -- 888}, year = {2017}, abstract = {The recent series 5 of the Answer Set Programming (ASP) system clingo provides generic means to enhance basic ASP with theory reasoning capabilities. We instantiate this framework with different forms of linear constraints and elaborate upon its formal properties. Given this, we discuss the respective implementations, and present techniques for using these constraints in a reactive context. More precisely, we introduce extensions to clingo with difference and linear constraints over integers and reals, respectively, and realize them in complementary ways. Finally, we empirically evaluate the resulting clingo derivatives clingo[dl] and clingo[lp] on common language fragments and contrast them to related ASP systems.}, language = {en} } @article{HoosKaminskiLindaueretal.2015, author = {Hoos, Holger and Kaminski, Roland and Lindauer, Marius and Schaub, Torsten H.}, title = {aspeed: Solver scheduling via answer set programming}, series = {Theory and practice of logic programming}, volume = {15}, journal = {Theory and practice of logic programming}, publisher = {Cambridge Univ. Press}, address = {New York}, issn = {1471-0684}, doi = {10.1017/S1471068414000015}, pages = {117 -- 142}, year = {2015}, abstract = {Although Boolean Constraint Technology has made tremendous progress over the last decade, the efficacy of state-of-the-art solvers is known to vary considerably across different types of problem instances, and is known to depend strongly on algorithm parameters. This problem was addressed by means of a simple, yet effective approach using handmade, uniform, and unordered schedules of multiple solvers in ppfolio, which showed very impressive performance in the 2011 Satisfiability Testing (SAT) Competition. Inspired by this, we take advantage of the modeling and solving capacities of Answer Set Programming (ASP) to automatically determine more refined, that is, nonuniform and ordered solver schedules from the existing benchmarking data. We begin by formulating the determination of such schedules as multi-criteria optimization problems and provide corresponding ASP encodings. The resulting encodings are easily customizable for different settings, and the computation of optimum schedules can mostly be done in the blink of an eye, even when dealing with large runtime data sets stemming from many solvers on hundreds to thousands of instances. Also, the fact that our approach can be customized easily enabled us to swiftly adapt it to generate parallel schedules for multi-processor machines.}, language = {en} } @misc{HoosKaminskiLindaueretal.2015, author = {Hoos, Holger and Kaminski, Roland and Lindauer, Marius and Schaub, Torsten H.}, title = {aspeed}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {588}, issn = {1866-8372}, doi = {10.25932/publishup-41474}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-414743}, pages = {26}, year = {2015}, abstract = {Although Boolean Constraint Technology has made tremendous progress over the last decade, the efficacy of state-of-the-art solvers is known to vary considerably across different types of problem instances, and is known to depend strongly on algorithm parameters. This problem was addressed by means of a simple, yet effective approach using handmade, uniform, and unordered schedules of multiple solvers in ppfolio, which showed very impressive performance in the 2011 Satisfiability Testing (SAT) Competition. Inspired by this, we take advantage of the modeling and solving capacities of Answer Set Programming (ASP) to automatically determine more refined, that is, nonuniform and ordered solver schedules from the existing benchmarking data. We begin by formulating the determination of such schedules as multi-criteria optimization problems and provide corresponding ASP encodings. The resulting encodings are easily customizable for different settings, and the computation of optimum schedules can mostly be done in the blink of an eye, even when dealing with large runtime data sets stemming from many solvers on hundreds to thousands of instances. Also, the fact that our approach can be customized easily enabled us to swiftly adapt it to generate parallel schedules for multi-processor machines.}, language = {en} } @misc{GebserHarrisonKaminskietal.2015, author = {Gebser, Martin and Harrison, Amelia and Kaminski, Roland and Lifschitz, Vladimir and Schaub, Torsten H.}, title = {Abstract gringo}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {592}, issn = {1866-8372}, doi = {10.25932/publishup-41475}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-414751}, pages = {15}, year = {2015}, abstract = {This paper defines the syntax and semantics of the input language of the ASP grounder gringo. The definition covers several constructs that were not discussed in earlier work on the semantics of that language, including intervals, pools, division of integers, aggregates with non-numeric values, and lparse-style aggregate expressions. The definition is abstract in the sense that it disregards some details related to representing programs by strings of ASCII characters. It serves as a specification for gringo from Version 4.5 on.}, language = {en} }