TY - JOUR A1 - Schaub, Torsten A1 - Woltran, Stefan T1 - Answer set programming unleashed! JF - Künstliche Intelligenz N2 - Answer Set Programming faces an increasing popularity for problem solving in various domains. While its modeling language allows us to express many complex problems in an easy way, its solving technology enables their effective resolution. In what follows, we detail some of the key factors of its success. Answer Set Programming [ASP; Brewka et al. Commun ACM 54(12):92–103, (2011)] is seeing a rapid proliferation in academia and industry due to its easy and flexible way to model and solve knowledge-intense combinatorial (optimization) problems. To this end, ASP offers a high-level modeling language paired with high-performance solving technology. As a result, ASP systems provide out-off-the-box, general-purpose search engines that allow for enumerating (optimal) solutions. They are represented as answer sets, each being a set of atoms representing a solution. The declarative approach of ASP allows a user to concentrate on a problem’s specification rather than the computational means to solve it. This makes ASP a prime candidate for rapid prototyping and an attractive tool for teaching key AI techniques since complex problems can be expressed in a succinct and elaboration tolerant way. This is eased by the tuning of ASP’s modeling language to knowledge representation and reasoning (KRR). The resulting impact is nicely reflected by a growing range of successful applications of ASP [Erdem et al. AI Mag 37(3):53–68, 2016; Falkner et al. Industrial applications of answer set programming. K++nstliche Intelligenz (2018)] Y1 - 2018 U6 - https://doi.org/10.1007/s13218-018-0550-z SN - 0933-1875 SN - 1610-1987 VL - 32 IS - 2-3 SP - 105 EP - 108 PB - Springer CY - Heidelberg ER - TY - GEN A1 - Brewka, Gerhard A1 - Schaub, Torsten A1 - Woltran, Stefan T1 - Interview with Gerhard Brewka T2 - Künstliche Intelligenz N2 - This interview with Gerhard Brewka was conducted by correspondance in May 2018. The question set was compiled by Torsten Schaub and Stefan Woltran. Y1 - 2018 U6 - https://doi.org/10.1007/s13218-018-0549-5 SN - 0933-1875 SN - 1610-1987 VL - 32 IS - 2-3 SP - 219 EP - 221 PB - Springer CY - Heidelberg ER - TY - GEN A1 - Schaub, Torsten A1 - Woltran, Stefan T1 - Special issue on answer set programming T2 - Künstliche Intelligenz Y1 - 2018 U6 - https://doi.org/10.1007/s13218-018-0554-8 SN - 0933-1875 SN - 1610-1987 VL - 32 IS - 2-3 SP - 101 EP - 103 PB - Springer CY - Heidelberg ER - TY - GEN A1 - Hoos, Holger A1 - Kaminski, Roland A1 - Lindauer, Marius A1 - Schaub, Torsten 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 - Kaminski, Roland A1 - Schaub, Torsten T1 - Complex optimization in answer set programming T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Preference handling and optimization are indispensable means for addressing nontrivial applications in Answer Set Programming (ASP). However, their implementation becomes difficult whenever they bring about a significant increase in computational complexity. As a consequence, existing ASP systems do not offer complex optimization capacities, supporting, for instance, inclusion-based minimization or Pareto efficiency. Rather, such complex criteria are typically addressed by resorting to dedicated modeling techniques, like saturation. Unlike the ease of common ASP modeling, however, these techniques are rather involved and hardly usable by ASP laymen. We address this problem by developing a general implementation technique by means of meta-prpogramming, thus reusing existing ASP systems to capture various forms of qualitative preferences among answer sets. In this way, complex preferences and optimization capacities become readily available for ASP applications. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 554 KW - answer set programming KW - preference handling KW - complex optimization KW - meta-programming Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-412436 SN - 1866-8372 IS - 554 ER - TY - GEN A1 - Gebser, Martin A1 - Kaufmann, Benjamin A1 - Schaub, Torsten T1 - Multi-threaded ASP solving with clasp T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - We present the new multi-threaded version of the state-of-the-art answer set solver clasp. We detail its component and communication architecture and illustrate how they support the principal functionalities of clasp. Also, we provide some insights into the data representation used for different constraint types handled by clasp. All this is accompanied by an extensive experimental analysis of the major features related to multi-threading in clasp. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 586 KW - propositional satisfiability KW - clause elimination KW - parallel execution KW - SAT KW - algorithm KW - platypus KW - systems KW - search KW - solver Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-413977 SN - 1866-8372 IS - 586 ER - TY - GEN A1 - Durzinsky, Markus A1 - Marwan, Wolfgang A1 - Ostrowski, Max A1 - Schaub, Torsten A1 - Wagler, Annegret T1 - Automatic network reconstruction using ASP T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Building biological models by inferring functional dependencies from experimental data is an important issue in Molecular Biology. To relieve the biologist from this traditionally manual process, various approaches have been proposed to increase the degree of automation. However, available approaches often yield a single model only, rely on specific assumptions, and/or use dedicated, heuristic algorithms that are intolerant to changing circumstances or requirements in the view of the rapid progress made in Biotechnology. Our aim is to provide a declarative solution to the problem by appeal to Answer Set Programming (ASP) overcoming these difficulties. We build upon an existing approach to Automatic Network Reconstruction proposed by part of the authors. This approach has firm mathematical foundations and is well suited for ASP due to its combinatorial flavor providing a characterization of all models explaining a set of experiments. The usage of ASP has several benefits over the existing heuristic algorithms. First, it is declarative and thus transparent for biological experts. Second, it is elaboration tolerant and thus allows for an easy exploration and incorporation of biological constraints. Third, it allows for exploring the entire space of possible models. Finally, our approach offers an excellent performance, matching existing, special-purpose systems. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 560 KW - regulatory networks KW - biological networks KW - answer Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-412419 SN - 1866-8372 IS - 560 ER - TY - JOUR A1 - Dimopoulos, Yannis A1 - Gebser, Martin A1 - Lühne, Patrick A1 - Romero Davila, Javier A1 - Schaub, Torsten T1 - plasp 3 BT - Towards Effective ASP Planning JF - Theory and practice of logic programming N2 - We describe the new version of the Planning Domain Definition Language (PDDL)-to-Answer Set Programming (ASP) translator plasp. First, it widens the range of accepted PDDL features. Second, it contains novel planning encodings, some inspired by Satisfiability Testing (SAT) planning and others exploiting ASP features such as well-foundedness. All of them are designed for handling multivalued fluents in order to capture both PDDL as well as SAS planning formats. Third, enabled by multishot ASP solving, it offers advanced planning algorithms also borrowed from SAT planning. As a result, plasp provides us with an ASP-based framework for studying a variety of planning techniques in a uniform setting. Finally, we demonstrate in an empirical analysis that these techniques have a significant impact on the performance of ASP planning. KW - knowledge representation and nonmonotonic reasoning KW - technical notes and rapid communications KW - answer set programming KW - automated planning KW - action and change Y1 - 2019 U6 - https://doi.org/10.1017/S1471068418000583 SN - 1471-0684 SN - 1475-3081 VL - 19 IS - 3 SP - 477 EP - 504 PB - Cambridge Univ. Press CY - New York ER - TY - GEN A1 - Lifschitz, Vladimir A1 - Schaub, Torsten A1 - Woltran, Stefan T1 - Interview with Vladimir Lifschitz T2 - Künstliche Intelligenz N2 - This interview with Vladimir Lifschitz was conducted by Torsten Schaub at the University of Texas at Austin in August 2017. The question set was compiled by Torsten Schaub and Stefan Woltran. Y1 - 2018 U6 - https://doi.org/10.1007/s13218-018-0552-x SN - 0933-1875 SN - 1610-1987 VL - 32 IS - 2-3 SP - 213 EP - 218 PB - Springer CY - Heidelberg ER - TY - JOUR A1 - Gebser, Martin A1 - Kaminski, Roland A1 - Kaufmann, Benjamin A1 - Lühne, Patrick A1 - Obermeier, Philipp A1 - Ostrowski, Max A1 - Romero Davila, Javier A1 - Schaub, Torsten A1 - Schellhorn, Sebastian A1 - Wanko, Philipp T1 - The Potsdam Answer Set Solving Collection 5.0 JF - Künstliche Intelligenz N2 - The Potsdam answer set solving collection, or Potassco for short, bundles various tools implementing and/or applying answer set programming. The article at hand succeeds an earlier description of the Potassco project published in Gebser et al. (AI Commun 24(2):107-124, 2011). Hence, we concentrate in what follows on the major features of the most recent, fifth generation of the ASP system clingo and highlight some recent resulting application systems. Y1 - 2018 U6 - https://doi.org/10.1007/s13218-018-0528-x SN - 0933-1875 SN - 1610-1987 VL - 32 IS - 2-3 SP - 181 EP - 182 PB - Springer CY - Heidelberg ER -