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 - 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 - JOUR A1 - Gebser, Martin A1 - Sabuncu, Orkunt A1 - Schaub, Torsten H. T1 - An incremental answer set programming based system for finite model computation JF - AI communications : AICOM ; the European journal on artificial intelligence N2 - We address the problem of Finite Model Computation (FMC) of first-order theories and show that FMC can efficiently and transparently be solved by taking advantage of a recent extension of Answer Set Programming (ASP), called incremental Answer Set Programming (iASP). The idea is to use the incremental parameter in iASP programs to account for the domain size of a model. The FMC problem is then successively addressed for increasing domain sizes until an answer set, representing a finite model of the original first-order theory, is found. We implemented a system based on the iASP solver iClingo and demonstrate its competitiveness by showing that it slightly outperforms the winner of the FNT division of CADE's 2009 Automated Theorem Proving (ATP) competition on the respective benchmark collection. KW - Incremental answer set programming KW - finite model computation Y1 - 2011 U6 - https://doi.org/10.3233/AIC-2011-0496 SN - 0921-7126 VL - 24 IS - 2 SP - 195 EP - 212 PB - IOS Press CY - Amsterdam ER - TY - JOUR A1 - Anger, Christian A1 - Gebser, Martin A1 - Schaub, Torsten H. T1 - Approaching the core of unfounded sets Y1 - 2006 UR - http://www.cs.uni-potsdam.de/wv/pdfformat/angesc06a.pdf ER - TY - GEN A1 - Schäpers, Björn A1 - Niemueller, Tim A1 - Lakemeyer, Gerhard A1 - Gebser, Martin A1 - Schaub, Torsten H. T1 - ASP-Based Time-Bounded Planning for Logistics Robots T2 - Twenty-Eighth International Conference on Automated Planning and Scheduling (ICAPS 2018) N2 - Manufacturing industries are undergoing a major paradigm shift towards more autonomy. Automated planning and scheduling then becomes a necessity. The Planning and Execution Competition for Logistics Robots in Simulation held at ICAPS is based on this scenario and provides an interesting testbed. However, the posed problem is challenging as also demonstrated by the somewhat weak results in 2017. The domain requires temporal reasoning and dealing with uncertainty. We propose a novel planning system based on Answer Set Programming and the Clingo solver to tackle these problems and incentivize robot cooperation. Our results show a significant performance improvement, both, in terms of lowering computational requirements and better game metrics. Y1 - 2018 SN - 2334-0835 SN - 2334-0843 SP - 509 EP - 517 PB - ASSOC Association for the Advancement of Artificial Intelligence CY - Palo Alto ER - TY - JOUR A1 - Gebser, Martin A1 - Kaufmann, Benjamin A1 - Neumann, André A1 - Schaub, Torsten H. T1 - Clasp : a conflict-driven answer set solver Y1 - 2007 SN - 978-3-540- 72199-4 ER - TY - JOUR A1 - Gebser, Martin A1 - Kaminski, Roland A1 - Schaub, Torsten H. T1 - Complex optimization in answer set programming JF - Theory and practice of logic programming 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. KW - Answer Set Programming KW - Preference Handling KW - Complex optimization KW - Meta-Programming Y1 - 2011 U6 - https://doi.org/10.1017/S1471068411000329 SN - 1471-0684 VL - 11 IS - 3 SP - 821 EP - 839 PB - Cambridge Univ. Press CY - New York ER - TY - JOUR A1 - Gebser, Martin A1 - Kaufmann, Benjamin A1 - Neumann, André A1 - Schaub, Torsten H. T1 - Conflict-driven answer set enumeration Y1 - 2007 SN - 978-3-540- 72199-4 ER - TY - JOUR A1 - Gebser, Martin A1 - Kaufmann, Benjamin A1 - Neumann, André A1 - Schaub, Torsten H. T1 - Conflict-driven answer set solving Y1 - 2007 SN - 978-1-57735-323-2 ER - TY - JOUR A1 - Gebser, Martin A1 - Kaufmann, Benjamin A1 - Schaub, Torsten H. T1 - Conflict-driven answer set solving: From theory to practice JF - Artificial intelligence N2 - We introduce an approach to computing answer sets of logic programs, based on concepts successfully applied in Satisfiability (SAT) checking. The idea is to view inferences in Answer Set Programming (ASP) as unit propagation on nogoods. This provides us with a uniform constraint-based framework capturing diverse inferences encountered in ASP solving. Moreover, our approach allows us to apply advanced solving techniques from the area of SAT. As a result, we present the first full-fledged algorithmic framework for native conflict-driven ASP solving. Our approach is implemented in the ASP solver clasp that has demonstrated its competitiveness and versatility by winning first places at various solver contests. KW - Answer set programming KW - Logic programming KW - Nonmonotonic reasoning Y1 - 2012 U6 - https://doi.org/10.1016/j.artint.2012.04.001 SN - 0004-3702 VL - 187 IS - 8 SP - 52 EP - 89 PB - Elsevier CY - Amsterdam 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 - Janhunen, Tomi A1 - Rintanen, Jussi T1 - Declarative encodings of acyclicity properties JF - Journal of logic and computation N2 - Many knowledge representation tasks involve trees or similar structures as abstract datatypes. However, devising compact and efficient declarative representations of such structural properties is non-obvious and can be challenging indeed. In this article, we take a number of acyclicity properties into consideration and investigate various logic-based approaches to encode them. We use answer set programming as the primary representation language but also consider mappings to related formalisms, such as propositional logic, difference logic and linear programming. We study the compactness of encodings and the resulting computational performance on benchmarks involving acyclic or tree structures. KW - acyclicity properties KW - logic-based modeling KW - answer set programming KW - satisfiability Y1 - 2015 U6 - https://doi.org/10.1093/logcom/exv063 SN - 0955-792X SN - 1465-363X VL - 30 IS - 4 SP - 923 EP - 952 PB - Oxford Univ. Press CY - Eynsham, Oxford ER - TY - JOUR A1 - Gebser, Martin A1 - Schaub, Torsten H. A1 - Thiele, Sven A1 - Veber, Philippe T1 - Detecting inconsistencies in large biological networks with answer set programming JF - Theory and practice of logic programming N2 - We introduce an approach to detecting inconsistencies in large biological networks by using answer set programming. To this end, we build upon a recently proposed notion of consistency between biochemical/genetic reactions and high-throughput profiles of cell activity. We then present an approach based on answer set programming to check the consistency of large-scale data sets. Moreover, we extend this methodology to provide explanations for inconsistencies by determining minimal representations of conflicts. In practice, this can be used to identify unreliable data or to indicate missing reactions. KW - answer set programming KW - bioinformatics KW - consistency KW - diagnosis Y1 - 2011 U6 - https://doi.org/10.1017/S1471068410000554 SN - 1471-0684 VL - 11 IS - 5-6 SP - 323 EP - 360 PB - Cambridge Univ. Press CY - New York ER - TY - JOUR A1 - Gebser, Martin A1 - Schaub, Torsten H. T1 - Generic tableaux for answer set programming Y1 - 2007 ER - TY - JOUR A1 - Gebser, Martin A1 - Schaub, Torsten H. A1 - Thiele, Sven T1 - GrinGo : a new grounder for answer set programming Y1 - 2007 SN - 978-3-540- 72199-4 ER - TY - JOUR A1 - Gebser, Martin A1 - Lee, Joohyung A1 - Lierler, Yuliya T1 - Head-elementary-set-free logic programs Y1 - 2007 SN - 978-3-540- 72199-4 ER - TY - JOUR A1 - Gebser, Martin A1 - Gharib, Mona A1 - Schaub, Torsten H. T1 - Incremental answer sets and their computation Y1 - 2007 ER - TY - JOUR A1 - Videla, Santiago A1 - Guziolowski, Carito A1 - Eduati, Federica A1 - Thiele, Sven A1 - Gebser, Martin A1 - Nicolas, Jacques A1 - Saez-Rodriguez, Julio A1 - Schaub, Torsten H. A1 - Siegel, Anne T1 - Learning Boolean logic models of signaling networks with ASP JF - Theoretical computer science N2 - Boolean networks provide a simple yet powerful qualitative modeling approach in systems biology. However, manual identification of logic rules underlying the system being studied is in most cases out of reach. Therefore, automated inference of Boolean logical networks from experimental data is a fundamental question in this field. This paper addresses the problem consisting of learning from a prior knowledge network describing causal interactions and phosphorylation activities at a pseudo-steady state, Boolean logic models of immediate-early response in signaling transduction networks. The underlying optimization problem has been so far addressed through mathematical programming approaches and the use of dedicated genetic algorithms. In a recent work we have shown severe limitations of stochastic approaches in this domain and proposed to use Answer Set Programming (ASP), considering a simpler problem setting. Herein, we extend our previous work in order to consider more realistic biological conditions including numerical datasets, the presence of feedback-loops in the prior knowledge network and the necessity of multi-objective optimization. In order to cope with such extensions, we propose several discretization schemes and elaborate upon our previous ASP encoding. Towards real-world biological data, we evaluate the performance of our approach over in silico numerical datasets based on a real and large-scale prior knowledge network. The correctness of our encoding and discretization schemes are dealt with in Appendices A-B. (C) 2014 Elsevier B.V. All rights reserved. KW - Answer set programming KW - Signaling transduction networks KW - Boolean logic models KW - Combinatorial multi-objective optimization KW - Systems biology Y1 - 2015 U6 - https://doi.org/10.1016/j.tcs.2014.06.022 SN - 0304-3975 SN - 1879-2294 VL - 599 SP - 79 EP - 101 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Gebser, Martin A1 - Gharib, Mona A1 - Mercer, Robert E. A1 - Schaub, Torsten H. T1 - Monotonic answer set programming N2 - Answer set programming (ASP) does not allow for incrementally constructing answer sets or locally validating constructions like proofs by only looking at a part of the given program. In this article, we elaborate upon an alternative approach to ASP that allows for incremental constructions. Our approach draws its basic intuitions from the area of default logics. We investigate the feasibility of the concept of semi-monotonicity known from default logics as a basis of incrementality. On the one hand, every logic program has at least one answer set in our alternative setting, which moreover can be constructed incrementally based on generating rules. On the other hand, the approach may produce answer sets lacking characteristic properties of standard answer sets, such as being a model of the given program. We show how integrity constraints can be used to re-establish such properties, even up to correspondence with standard answer sets. Furthermore, we develop an SLD-like proof procedure for our incremental approach to ASP, which allows for query-oriented computations. Also, we provide a characterization of our definition of answer sets via a modification of Clarks completion. Based on this notion of program completion, we present an algorithm for computing the answer sets of a logic program in our approach. Y1 - 2009 UR - http://logcom.oxfordjournals.org/ U6 - https://doi.org/10.1093/logcom/exn040 SN - 0955-792X ER - TY - JOUR A1 - Gebser, Martin A1 - Kaufmann, Benjamin A1 - Schaub, Torsten H. T1 - Multi-threaded ASP solving with clasp JF - Theory and practice of logic programming 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. Y1 - 2012 U6 - https://doi.org/10.1017/S1471068412000166 SN - 1471-0684 VL - 12 IS - 8 SP - 525 EP - 545 PB - Cambridge Univ. Press CY - New York ER - TY - JOUR A1 - Gebser, Martin A1 - Lee, Joohyung A1 - Lierler, Yuliya T1 - On elementary loops of logic programs JF - Theory and practice of logic programming N2 - Using the notion of an elementary loop, Gebser and Schaub (2005. Proceedings of the Eighth International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR'05), 53-65) refined the theorem on loop formulas attributable to Lin and Zhao (2004) by considering loop formulas of elementary loops only. In this paper, we reformulate the definition of an elementary loop, extend it to disjunctive programs, and study several properties of elementary loops, including how maximal elementary loops are related to minimal unfounded sets. The results provide useful insights into the stable model semantics in terms of elementary loops. For a nondisjunctive program, using a graph-theoretic characterization of an elementary loop, we show that the problem of recognizing an elementary loop is tractable. On the other hand, we also show that the corresponding problem is coNP-complete for a disjunctive program. Based on the notion of an elementary loop, we present the class of Head-Elementary-loop-Free (HEF) programs, which strictly generalizes the class of Head-Cycle-Free (HCF) programs attributable to Ben-Eliyahu and Dechter (1994. Annals of Mathematics and Artificial Intelligence 12, 53-87). Like an Ha: program, an HEF program can be turned into an equivalent nondisjunctive program in polynomial time by shifting head atoms into the body. KW - stable model semantics KW - loop formulas KW - unfounded sets Y1 - 2011 U6 - https://doi.org/10.1017/S1471068411000019 SN - 1471-0684 VL - 11 IS - 2 SP - 953 EP - 988 PB - Cambridge Univ. Press CY - New York ER - TY - JOUR A1 - Dimopoulos, Yannis A1 - Gebser, Martin A1 - Lühne, Patrick A1 - Romero Davila, Javier A1 - Schaub, Torsten H. 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 - JOUR A1 - Gebser, Martin A1 - Kaufmann, Benjamin A1 - Kaminski, Roland A1 - Ostrowski, Max A1 - Schaub, Torsten H. A1 - Schneider, Marius T1 - Potassco the Potsdam answer set solving collection JF - AI communications : AICOM ; the European journal on artificial intelligence N2 - This paper gives an overview of the open source project Potassco, the Potsdam Answer Set Solving Collection, bundling tools for Answer Set Programming developed at the University of Potsdam. KW - Answer set programming KW - declarative problem solving Y1 - 2011 U6 - https://doi.org/10.3233/AIC-2011-0491 SN - 0921-7126 VL - 24 IS - 2 SP - 107 EP - 124 PB - IOS Press CY - Amsterdam ER - TY - THES A1 - Gebser, Martin T1 - Proof theory and algorithms for answer set programming T1 - Beweistheorie und Algorithmen für die Antwortmengenprogrammierung N2 - Answer Set Programming (ASP) is an emerging paradigm for declarative programming, in which a computational problem is specified by a logic program such that particular models, called answer sets, match solutions. ASP faces a growing range of applications, demanding for high-performance tools able to solve complex problems. ASP integrates ideas from a variety of neighboring fields. In particular, automated techniques to search for answer sets are inspired by Boolean Satisfiability (SAT) solving approaches. While the latter have firm proof-theoretic foundations, ASP lacks formal frameworks for characterizing and comparing solving methods. Furthermore, sophisticated search patterns of modern SAT solvers, successfully applied in areas like, e.g., model checking and verification, are not yet established in ASP solving. We address these deficiencies by, for one, providing proof-theoretic frameworks that allow for characterizing, comparing, and analyzing approaches to answer set computation. For another, we devise modern ASP solving algorithms that integrate and extend state-of-the-art techniques for Boolean constraint solving. We thus contribute to the understanding of existing ASP solving approaches and their interconnections as well as to their enhancement by incorporating sophisticated search patterns. The central idea of our approach is to identify atomic as well as composite constituents of a propositional logic program with Boolean variables. This enables us to describe fundamental inference steps, and to selectively combine them in proof-theoretic characterizations of various ASP solving methods. In particular, we show that different concepts of case analyses applied by existing ASP solvers implicate mutual exponential separations regarding their best-case complexities. We also develop a generic proof-theoretic framework amenable to language extensions, and we point out that exponential separations can likewise be obtained due to case analyses on them. We further exploit fundamental inference steps to derive Boolean constraints characterizing answer sets. They enable the conception of ASP solving algorithms including search patterns of modern SAT solvers, while also allowing for direct technology transfers between the areas of ASP and SAT solving. Beyond the search for one answer set of a logic program, we address the enumeration of answer sets and their projections to a subvocabulary, respectively. The algorithms we develop enable repetition-free enumeration in polynomial space without being intrusive, i.e., they do not necessitate any modifications of computations before an answer set is found. Our approach to ASP solving is implemented in clasp, a state-of-the-art Boolean constraint solver that has successfully participated in recent solver competitions. Although we do here not address the implementation techniques of clasp or all of its features, we present the principles of its success in the context of ASP solving. N2 - Antwortmengenprogrammierung (engl. Answer Set Programming; ASP) ist ein Paradigma zum deklarativen Problemlösen, wobei Problemstellungen durch logische Programme beschrieben werden, sodass bestimmte Modelle, Antwortmengen genannt, zu Lösungen korrespondieren. Die zunehmenden praktischen Anwendungen von ASP verlangen nach performanten Werkzeugen zum Lösen komplexer Problemstellungen. ASP integriert diverse Konzepte aus verwandten Bereichen. Insbesondere sind automatisierte Techniken für die Suche nach Antwortmengen durch Verfahren zum Lösen des aussagenlogischen Erfüllbarkeitsproblems (engl. Boolean Satisfiability; SAT) inspiriert. Letztere beruhen auf soliden beweistheoretischen Grundlagen, wohingegen es für ASP kaum formale Systeme gibt, um Lösungsmethoden einheitlich zu beschreiben und miteinander zu vergleichen. Weiterhin basiert der Erfolg moderner Verfahren zum Lösen von SAT entscheidend auf fortgeschrittenen Suchtechniken, die in gängigen Methoden zur Antwortmengenberechnung nicht etabliert sind. Diese Arbeit entwickelt beweistheoretische Grundlagen und fortgeschrittene Suchtechniken im Kontext der Antwortmengenberechnung. Unsere formalen Beweissysteme ermöglichen die Charakterisierung, den Vergleich und die Analyse vorhandener Lösungsmethoden für ASP. Außerdem entwerfen wir moderne Verfahren zum Lösen von ASP, die fortgeschrittene Suchtechniken aus dem SAT-Bereich integrieren und erweitern. Damit trägt diese Arbeit sowohl zum tieferen Verständnis von Lösungsmethoden für ASP und ihrer Beziehungen untereinander als auch zu ihrer Verbesserung durch die Erschließung fortgeschrittener Suchtechniken bei. Die zentrale Idee unseres Ansatzes besteht darin, Atome und komposite Konstrukte innerhalb von logischen Programmen gleichermaßen mit aussagenlogischen Variablen zu assoziieren. Dies ermöglicht die Isolierung fundamentaler Inferenzschritte, die wir in formalen Charakterisierungen von Lösungsmethoden für ASP selektiv miteinander kombinieren können. Darauf aufbauend zeigen wir, dass unterschiedliche Einschränkungen von Fallunterscheidungen zwangsläufig zu exponentiellen Effizienzunterschieden zwischen den charakterisierten Methoden führen. Wir generalisieren unseren beweistheoretischen Ansatz auf logische Programme mit erweiterten Sprachkonstrukten und weisen analytisch nach, dass das Treffen bzw. Unterlassen von Fallunterscheidungen auf solchen Konstrukten ebenfalls exponentielle Effizienzunterschiede bedingen kann. Die zuvor beschriebenen fundamentalen Inferenzschritte nutzen wir zur Extraktion inhärenter Bedingungen, denen Antwortmengen genügen müssen. Damit schaffen wir eine Grundlage für den Entwurf moderner Lösungsmethoden für ASP, die fortgeschrittene, ursprünglich für SAT konzipierte, Suchtechniken mit einschließen und darüber hinaus einen transparenten Technologietransfer zwischen Verfahren zum Lösen von ASP und SAT erlauben. Neben der Suche nach einer Antwortmenge behandeln wir ihre Aufzählung, sowohl für gesamte Antwortmengen als auch für Projektionen auf ein Subvokabular. Hierfür entwickeln wir neuartige Methoden, die wiederholungsfreies Aufzählen in polynomiellem Platz ermöglichen, ohne die Suche zu beeinflussen und ggf. zu behindern, bevor Antwortmengen berechnet wurden. KW - Wissensrepräsentation und -verarbeitung KW - Antwortmengenprogrammierung KW - Beweistheorie KW - Algorithmen KW - Knowledge Representation and Reasoning KW - Answer Set Programming KW - Proof Theory KW - Algorithms Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-55425 ER - TY - JOUR A1 - Gebser, Martin A1 - Obermeier, Philipp A1 - Schaub, Torsten H. A1 - Ratsch-Heitmann, Michel A1 - Runge, Mario T1 - Routing driverless transport vehicles in car assembly with answer set programming JF - Theory and practice of logic programming N2 - Automated storage and retrieval systems are principal components of modern production and warehouse facilities. In particular, automated guided vehicles nowadays substitute human-operated pallet trucks in transporting production materials between storage locations and assembly stations. While low-level control systems take care of navigating such driverless vehicles along programmed routes and avoid collisions even under unforeseen circumstances, in the common case of multiple vehicles sharing the same operation area, the problem remains how to set up routes such that a collection of transport tasks is accomplished most effectively. We address this prevalent problem in the context of car assembly at Mercedes-Benz Ludwigsfelde GmbH, a large-scale producer of commercial vehicles, where routes for automated guided vehicles used in the production process have traditionally been hand-coded by human engineers. Such adhoc methods may suffice as long as a running production process remains in place, while any change in the factory layout or production targets necessitates tedious manual reconfiguration, not to mention the missing portability between different production plants. Unlike this, we propose a declarative approach based on Answer Set Programming to optimize the routes taken by automated guided vehicles for accomplishing transport tasks. The advantages include a transparent and executable problem formalization, provable optimality of routes relative to objective criteria, as well as elaboration tolerance towards particular factory layouts and production targets. Moreover, we demonstrate that our approach is efficient enough to deal with the transport tasks evolving in realistic production processes at the car factory of Mercedes-Benz Ludwigsfelde GmbH. KW - automated guided vehicle routing KW - car assembly operations KW - answer set programming Y1 - 2018 U6 - https://doi.org/10.1017/S1471068418000182 SN - 1471-0684 SN - 1475-3081 VL - 18 IS - 3-4 SP - 520 EP - 534 PB - Cambridge Univ. Press CY - New York ER - TY - JOUR A1 - Gebser, Martin A1 - Schaub, Torsten H. T1 - Tableau calculi for logic programs under answer set semantics JF - ACM transactions on computational logic N2 - We introduce formal proof systems based on tableau methods for analyzing computations in Answer Set Programming (ASP). Our approach furnishes fine-grained instruments for characterizing operations as well as strategies of ASP solvers. The granularity is detailed enough to capture a variety of propagation and choice methods of algorithms used for ASP solving, also incorporating SAT-based and conflict-driven learning approaches to some extent. This provides us with a uniform setting for identifying and comparing fundamental properties of ASP solving approaches. In particular, we investigate their proof complexities and show that the run-times of best-case computations can vary exponentially between different existing ASP solvers. Apart from providing a framework for comparing ASP solving approaches, our characterizations also contribute to their understanding by pinning down the constitutive atomic operations. Furthermore, our framework is flexible enough to integrate new inference patterns, and so to study their relation to existing ones. To this end, we generalize our approach and provide an extensible basis aiming at a modular incorporation of additional language constructs. This is exemplified by augmenting our basic tableau methods with cardinality constraints and disjunctions. KW - Theory KW - Answer Set Programming KW - tableau calculi KW - proof complexity Y1 - 2013 U6 - https://doi.org/10.1145/2480759.2480767 SN - 1529-3785 VL - 14 IS - 2 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Gebser, Martin A1 - Liu, Lengning A1 - Namasivayam, Gayathri A1 - Neumann, André A1 - Schaub, Torsten H. A1 - Truszczynski, Miroslaw T1 - The first answer set programming system competition Y1 - 2007 SN - 978-3-540- 72199-4 ER - TY - JOUR A1 - Anger, Christian A1 - Gebser, Martin A1 - Linke, Thomas A1 - Neumann, Andre A1 - Schaub, Torsten H. T1 - The nomore++ approach to answer set solving Y1 - 2005 UR - http://www.cs.uni-potsdam.de/wv/pdfformat/angelinesc05c.pdf ER - TY - JOUR A1 - Anger, Christian A1 - Gebser, Martin A1 - Linke, Thomas A1 - Neumann, Andre A1 - Schaub, Torsten H. T1 - The nomore++ approach to answer set solving Y1 - 2005 UR - http://www.cs.uni-potsdam.de/wv/pdfformat/angelinesc05c.pdf 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 H. 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 - TY - JOUR A1 - Gebser, Martin A1 - Maratea, Marco A1 - Ricca, Francesco T1 - The Seventh Answer Set Programming Competition BT - design and results JF - Theory and practice of logic programming N2 - Answer Set Programming (ASP) is a prominent knowledge representation language with roots in logic programming and non-monotonic reasoning. Biennial ASP competitions are organized in order to furnish challenging benchmark collections and assess the advancement of the state of the art in ASP solving. In this paper, we report on the design and results of the Seventh ASP Competition, jointly organized by the University of Calabria (Italy), the University of Genova (Italy), and the University of Potsdam (Germany), in affiliation with the 14th International Conference on Logic Programming and Non-Monotonic Reasoning (LPNMR 2017). KW - Answer Set Programming KW - competition Y1 - 2019 U6 - https://doi.org/10.1017/S1471068419000061 SN - 1471-0684 SN - 1475-3081 VL - 20 IS - 2 SP - 176 EP - 204 PB - Cambridge Univ. Press CY - Cambridge [u.a.] ER - TY - JOUR A1 - Gebser, Martin A1 - Maratea, Marco A1 - Ricca, Francesco T1 - The sixth answer set programming competition JF - Journal of artificial intelligence research : JAIR N2 - Answer Set Programming (ASP) is a well-known paradigm of declarative programming with roots in logic programming and non-monotonic reasoning. Similar to other closely related problemsolving technologies, such as SAT/SMT, QBF, Planning and Scheduling, advancements in ASP solving are assessed in competition events. In this paper, we report about the design and results of the Sixth ASP Competition, which was jointly organized by the University of Calabria (Italy), Aalto University (Finland), and the University of Genoa (Italy), in affiliation with the 13th International Conference on Logic Programming and Non-Monotonic Reasoning. This edition maintained some of the design decisions introduced in 2014, e.g., the conception of sub-tracks, the scoring scheme,and the adherence to a fixed modeling language in order to push the adoption of the ASP-Core-2 standard. On the other hand, it featured also some novelties, like a benchmark selection stage classifying instances according to their empirical hardness, and a “Marathon” track where the topperforming systems are given more time for solving hard benchmarks. Y1 - 2017 U6 - https://doi.org/10.1613/jair.5373 SN - 1076-9757 SN - 1943-5037 VL - 60 SP - 41 EP - 95 PB - AI Access Found. CY - Marina del Rey ER - TY - JOUR A1 - Anger, Christian A1 - Gebser, Martin A1 - Janhunen, Tomi A1 - Schaub, Torsten H. T1 - What's a head without a body? Y1 - 2006 ER - TY - CHAP A1 - Gebser, Martin A1 - Hinrichs, Henrik A1 - Schaub, Torsten H. A1 - Thiele, Sven T1 - xpanda: a (simple) preprocessor for adding multi-valued propositions to ASP N2 - We introduce a simple approach extending the input language of Answer Set Programming (ASP) systems by multi-valued propositions. Our approach is implemented as a (prototypical) preprocessor translating logic programs with multi-valued propositions into logic programs with Boolean propositions only. Our translation is modular and heavily benefits from the expressive input language of ASP. The resulting approach, along with its implementation, allows for solving interesting constraint satisfaction problems in ASP, showing a good performance. Y1 - 2010 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-41466 ER -