TY - JOUR A1 - Janhunen, Tomi A1 - Kaminski, Roland A1 - Ostrowski, Max A1 - Schellhorn, Sebastian A1 - Wanko, Philipp A1 - Schaub, Torsten H. T1 - Clingo goes linear constraints over reals and integers JF - Theory and practice of logic programming N2 - 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. KW - Constraint Answer Set Programming (CASP) KW - Answer Set Programming (ASP) KW - Constraint Processing (CP) KW - Theory Solving Y1 - 2017 U6 - https://doi.org/10.1017/S1471068417000242 SN - 1471-0684 SN - 1475-3081 VL - 17 SP - 872 EP - 888 PB - Cambridge Univ. Press CY - New York ER - TY - JOUR A1 - Hoos, Holger A1 - Kaminski, Roland A1 - Lindauer, Marius A1 - Schaub, Torsten H. T1 - aspeed: Solver scheduling via answer set programming JF - Theory and practice of logic programming N2 - 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. KW - algorithm schedules KW - answer set programming KW - portfolio-based solving Y1 - 2015 U6 - https://doi.org/10.1017/S1471068414000015 SN - 1471-0684 SN - 1475-3081 VL - 15 SP - 117 EP - 142 PB - Cambridge Univ. Press CY - New York ER - TY - GEN A1 - Hoos, Holger A1 - Kaminski, Roland A1 - Lindauer, Marius A1 - Schaub, Torsten H. T1 - aspeed BT - solver scheduling via answer set programming T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 588 KW - algorithm schedules KW - answer set programming KW - portfolio-based solving Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-414743 SN - 1866-8372 IS - 588 ER - TY - GEN A1 - Gebser, Martin A1 - Harrison, Amelia A1 - Kaminski, Roland A1 - Lifschitz, Vladimir A1 - Schaub, Torsten H. T1 - Abstract gringo T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 592 KW - nested expressions Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-414751 SN - 1866-8372 IS - 592 ER -