TY - JOUR A1 - Sarsakov, Vladimir A1 - Schaub, Torsten H. A1 - Tompits, Hans A1 - Woltran, Stefan T1 - A compiler for nested logic programming Y1 - 2004 SN - 3-540- 20721-x ER - TY - JOUR A1 - Linke, Thomas A1 - Tompits, Hans A1 - Woltran, Stefan T1 - On Acyclic and head-cycle free nested logic programs Y1 - 2004 SN - 3-540-22671-01 ER - TY - JOUR A1 - Linke, Thomas A1 - Tompits, Hans A1 - Woltran, Stefan T1 - On acyclic and head-cycle free nested logic programs Y1 - 2004 ER - TY - JOUR A1 - Delgrande, James Patrick A1 - Schaub, Torsten H. A1 - Tompits, Hans A1 - Woltran, Stefan T1 - On Computing belief change operations using quantifield boolean formulas N2 - In this paper, we show how an approach to belief revision and belief contraction can be axiomatized by means of quantified Boolean formulas. Specifically, we consider the approach of belief change scenarios, a general framework that has been introduced for expressing different forms of belief change. The essential idea is that for a belief change scenario (K, R, C), the set of formulas K, representing the knowledge base, is modified so that the sets of formulas R and C are respectively true in, and consistent with the result. By restricting the form of a belief change scenario, one obtains specific belief change operators including belief revision, contraction, update, and merging. For both the general approach and for specific operators, we give a quantified Boolean formula such that satisfying truth assignments to the free variables correspond to belief change extensions in the original approach. Hence, we reduce the problem of determining the results of a belief change operation to that of satisfiability. This approach has several benefits. First, it furnishes an axiomatic specification of belief change with respect to belief change scenarios. This then leads to further insight into the belief change framework. Second, this axiomatization allows us to identify strict complexity bounds for the considered reasoning tasks. Third, we have implemented these different forms of belief change by means of existing solvers for quantified Boolean formulas. As well, it appears that this approach may be straightforwardly applied to other specific approaches to belief change Y1 - 2004 SN - 0955-792X ER - TY - JOUR A1 - Delgrande, James Patrick A1 - Schaub, Torsten H. A1 - Tompits, Hans A1 - Woltran, Stefan T1 - On computing solutions to belief change scenarios Y1 - 2001 SN - 3-540- 42464-4 ER - TY - JOUR A1 - Pearce, David A1 - Sarsakov, Vladimir A1 - Schaub, Torsten H. A1 - Tompits, Hans A1 - Woltran, Stefan T1 - A polynomial translation of logic programs with nested expressions into disjunctive logic programs Y1 - 2002 SN - 3-540-43930-7 ER - TY - JOUR A1 - Besnard, Philippe A1 - Schaub, Torsten H. A1 - Tompits, Hans A1 - Woltran, Stefan T1 - Paraconsistent reasoning via quantified boolean formulas Y1 - 2002 SN - 3-540-44190-5 ER - TY - JOUR A1 - Brain, Martin A1 - Gebser, Martin A1 - Pührer, Jörg A1 - Schaub, Torsten H. A1 - Tompits, Hans A1 - Woltran, Stefan T1 - "That is illogical, Captain!" : the debugging support tool spock for answer-set programs ; system description Y1 - 2007 ER - TY - JOUR A1 - Pearce, David A1 - Sarsakov, Vladimir A1 - Schaub, Torsten H. A1 - Tompits, Hans A1 - Woltran, Stefan T1 - A polynomial translation of logic programs with nested expressions into disjunctive logic programs : preliminary report Y1 - 2002 ER - TY - JOUR A1 - Schaub, Torsten H. 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 - JOUR A1 - Abseher, Michael A1 - Musliu, Nysret A1 - Woltran, Stefan A1 - Gebser, Martin A1 - Schaub, Torsten H. T1 - Shift Design with Answer Set Programming JF - Fundamenta informaticae N2 - Answer Set Programming (ASP) is a powerful declarative programming paradigm that has been successfully applied to many different domains. Recently, ASP has also proved successful for hard optimization problems like course timetabling and travel allotment. In this paper, we approach another important task, namely, the shift design problem, aiming at an alignment of a minimum number of shifts in order to meet required numbers of employees (which typically vary for different time periods) in such a way that over- and understaffing is minimized. We provide an ASP encoding of the shift design problem, which, to the best of our knowledge, has not been addressed by ASP yet. Our experimental results demonstrate that ASP is capable of improving the best known solutions to some benchmark problems. Other instances remain challenging and make the shift design problem an interesting benchmark for ASP-based optimization methods. Y1 - 2016 U6 - https://doi.org/10.3233/FI-2016-1396 SN - 0169-2968 SN - 1875-8681 VL - 147 SP - 1 EP - 25 PB - IOS Press CY - Amsterdam ER - TY - GEN A1 - Schaub, Torsten H. 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 - JOUR A1 - Besnard, Philippe A1 - Schaub, Torsten H. A1 - Tompits, Hans A1 - Woltran, Stefan T1 - Paraconsistent reasoning via quantified boolean formulas : Part II: Circumscribing inconsistent theories Y1 - 2003 SN - 3-540- 409494-5 ER - TY - GEN A1 - Fichte, Johannes Klaus A1 - Truszczynski, Miroslaw A1 - Woltran, Stefan T1 - Dual-normal logic programs BT - the forgotten class T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Disjunctive Answer Set Programming is a powerful declarative programming paradigm with complexity beyond NP. Identifying classes of programs for which the consistency problem is in NP is of interest from the theoretical standpoint and can potentially lead to improvements in the design of answer set programming solvers. One of such classes consists of dual-normal programs, where the number of positive body atoms in proper rules is at most one. Unlike other classes of programs, dual-normal programs have received little attention so far. In this paper we study this class. We relate dual-normal programs to propositional theories and to normal programs by presenting several inter-translations. With the translation from dual-normal to normal programs at hand, we introduce the novel class of body-cycle free programs, which are in many respects dual to head-cycle free programs. We establish the expressive power of dual-normal programs in terms of SE- and UE-models, and compare them to normal programs. We also discuss the complexity of deciding whether dual-normal programs are strongly and uniformly equivalent. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 585 KW - answer set programming KW - classes of logic programs KW - strong and uniform equivalence KW - propositional satisfiability Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-414490 SN - 1866-8372 IS - 585 ER - TY - JOUR A1 - Delgrande, James A1 - Schaub, Torsten H. A1 - Tompits, Hans A1 - Woltran, Stefan T1 - A model-theoretic approach to belief change in answer set programming JF - ACM transactions on computational logic N2 - We address the problem of belief change in (nonmonotonic) logic programming under answer set semantics. Our formal techniques are analogous to those of distance-based belief revision in propositional logic. In particular, we build upon the model theory of logic programs furnished by SE interpretations, where an SE interpretation is a model of a logic program in the same way that a classical interpretation is a model of a propositional formula. Hence we extend techniques from the area of belief revision based on distance between models to belief change in logic programs. We first consider belief revision: for logic programs P and Q, the goal is to determine a program R that corresponds to the revision of P by Q, denoted P * Q. We investigate several operators, including (logic program) expansion and two revision operators based on the distance between the SE models of logic programs. It proves to be the case that expansion is an interesting operator in its own right, unlike in classical belief revision where it is relatively uninteresting. Expansion and revision are shown to satisfy a suite of interesting properties; in particular, our revision operators satisfy all or nearly all of the AGM postulates for revision. We next consider approaches for merging a set of logic programs, P-1,...,P-n. Again, our formal techniques are based on notions of relative distance between the SE models of the logic programs. Two approaches are examined. The first informally selects for each program P-i those models of P-i that vary the least from models of the other programs. The second approach informally selects those models of a program P-0 that are closest to the models of programs P-1,...,P-n. In this case, P-0 can be thought of as a set of database integrity constraints. We examine these operators with regards to how they satisfy relevant postulate sets. Last, we present encodings for computing the revision as well as the merging of logic programs within the same logic programming framework. This gives rise to a direct implementation of our approach in terms of off-the-shelf answer set solvers. These encodings also reflect the fact that our change operators do not increase the complexity of the base formalism. KW - Theory KW - Answer set programming KW - belief revision KW - belief merging KW - program encodings KW - strong equivalence Y1 - 2013 U6 - https://doi.org/10.1145/2480759.2480766 SN - 1529-3785 VL - 14 IS - 2 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Brain, Martin A1 - Gebser, Martin A1 - Pührer, Jörg A1 - Schaub, Torsten H. A1 - Tompits, Hans A1 - Woltran, Stefan T1 - Debugging ASP programs by means of ASP Y1 - 2007 SN - 978-3-540- 72199-4 ER - TY - JOUR A1 - Gebser, Martin A1 - Schaub, Torsten H. A1 - Tompits, Hans A1 - Woltran, Stefan T1 - Alternative characterizations for program equivalence under aswer-set semantics : a preliminary report Y1 - 2007 ER - TY - GEN A1 - Lifschitz, Vladimir A1 - Schaub, Torsten H. 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 - GEN A1 - Brewka, Gerhard A1 - Schaub, Torsten H. 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 -