TY - JOUR A1 - Kaminski, Roland A1 - Schaub, Torsten A1 - Siegel, Anne A1 - Videla, Santiago T1 - Minimal intervention strategies in logical signaling networks with ASP JF - Theory and practice of logic programming N2 - Proposing relevant perturbations to biological signaling networks is central to many problems in biology and medicine because it allows for enabling or disabling certain biological outcomes. In contrast to quantitative methods that permit fine-grained (kinetic) analysis, qualitative approaches allow for addressing large-scale networks. This is accomplished by more abstract representations such as logical networks. We elaborate upon such a qualitative approach aiming at the computation of minimal interventions in logical signaling networks relying on Kleene's three-valued logic and fixpoint semantics. We address this problem within answer set programming and show that it greatly outperforms previous work using dedicated algorithms. Y1 - 2013 U6 - https://doi.org/10.1017/S1471068413000422 SN - 1471-0684 VL - 13 SP - 675 EP - 690 PB - Cambridge Univ. Press CY - New York ER - TY - JOUR A1 - Schaub, Torsten A1 - Brüning, Stefan A1 - Nicolas, Pascal T1 - XRay : a prolog technology theorem prover for default reasoning: a system description Y1 - 1996 SN - 3-540-61511-3 ER - TY - JOUR A1 - Besnard, Philippe A1 - Schaub, Torsten T1 - A simple signed system for paraconsistent reasoning Y1 - 1996 SN - 3-540-61630-6 ER - TY - JOUR A1 - Gebser, Martin A1 - Schaub, Torsten A1 - Tompits, Hans A1 - Woltran, Stefan T1 - Alternative characterizations for program equivalence under aswer-set semantics : a preliminary report Y1 - 2007 ER - TY - THES A1 - Konczak, Kathrin T1 - Preferences in answer set programming T1 - Präferenzen in der Antwortmengenprogrammierung N2 - Answer Set Programming (ASP) emerged in the late 1990s as a new logic programming paradigm, having its roots in nonmonotonic reasoning, deductive databases, and logic programming with negation as failure. The basic idea of ASP is to represent a computational problem as a logic program whose answer sets correspond to solutions, and then to use an answer set solver for finding answer sets of the program. ASP is particularly suited for solving NP-complete search problems. Among these, we find applications to product configuration, diagnosis, and graph-theoretical problems, e.g. finding Hamiltonian cycles. On different lines of ASP research, many extensions of the basic formalism have been proposed. The most intensively studied one is the modelling of preferences in ASP. They constitute a natural and effective way of selecting preferred solutions among a plethora of solutions for a problem. For example, preferences have been successfully used for timetabling, auctioning, and product configuration. In this thesis, we concentrate on preferences within answer set programming. Among several formalisms and semantics for preference handling in ASP, we concentrate on ordered logic programs with the underlying D-, W-, and B-semantics. In this setting, preferences are defined among rules of a logic program. They select preferred answer sets among (standard) answer sets of the underlying logic program. Up to now, those preferred answer sets have been computed either via a compilation method or by meta-interpretation. Hence, the question comes up, whether and how preferences can be integrated into an existing ASP solver. To solve this question, we develop an operational graph-based framework for the computation of answer sets of logic programs. Then, we integrate preferences into this operational approach. We empirically observe that our integrative approach performs in most cases better than the compilation method or meta-interpretation. Another research issue in ASP are optimization methods that remove redundancies, as also found in database query optimizers. For these purposes, the rather recently suggested notion of strong equivalence for ASP can be used. If a program is strongly equivalent to a subprogram of itself, then one can always use the subprogram instead of the original program, a technique which serves as an effective optimization method. Up to now, strong equivalence has not been considered for logic programs with preferences. In this thesis, we tackle this issue and generalize the notion of strong equivalence to ordered logic programs. We give necessary and sufficient conditions for the strong equivalence of two ordered logic programs. Furthermore, we provide program transformations for ordered logic programs and show in how far preferences can be simplified. Finally, we present two new applications for preferences within answer set programming. First, we define new procedures for group decision making, which we apply to the problem of scheduling a group meeting. As a second new application, we reconstruct a linguistic problem appearing in German dialects within ASP. Regarding linguistic studies, there is an ongoing debate about how unique the rule systems of language are in human cognition. The reconstruction of grammatical regularities with tools from computer science has consequences for this debate: if grammars can be modelled this way, then they share core properties with other non-linguistic rule systems. N2 - Die Antwortmengenprogrammierung entwickelte sich in den späten 90er Jahren als neues Paradigma der logischen Programmierung und ist in den Gebieten des nicht-monotonen Schließens und der deduktiven Datenbanken verwurzelt. Dabei wird eine Problemstellung als logisches Programm repräsentiert, dessen Lösungen, die so genannten Antwortmengen, genau den Lösungen des ursprünglichen Problems entsprechen. Die Antwortmengenprogrammierung bildet ein geeignetes Fundament zur Repräsentation und zum Lösen von Entscheidungs- und Suchproblemen in der Komplexitätsklasse NP. Anwendungen finden wir unter anderem in der Produktkonfiguration, Diagnose und bei graphen-theoretischen Problemen, z.B. der Suche nach Hamiltonschen Kreisen. In den letzten Jahren wurden viele Erweiterungen der Antwortmengenprogrammierung betrachtet. Die am meisten untersuchte Erweiterung ist die Modellierung von Präferenzen. Diese bilden eine natürliche und effektive Möglichkeit, unter einer Vielzahl von Lösungen eines Problems bevorzugte Lösungen zu selektieren. Präferenzen finden beispielsweise in der Stundenplanung, bei Auktionen und bei Produktkonfigurationen ihre Anwendung. Der Schwerpunkt dieser Arbeit liegt in der Modellierung, Implementierung und Anwendung von Präferenzen in der Antwortmengenprogrammierung. Da es verschiedene Ansätze gibt, um Präferenzen darzustellen, konzentrieren wir uns auf geordnete logische Programme, wobei Präferenzen als partielle Ordnung der Regeln eines logischen Programms ausgedrückt werden. Dabei betrachten wir drei verschiedene Semantiken zur Interpretation dieser Präferenzen. Im Vorfeld wurden für diese Semantiken die bevorzugten Antwortmengen durch einen Compiler oder durch Meta-Interpretation berechnet. Da Präferenzen Lösungen selektieren, stellt sich die Frage, ob es möglich ist, diese direkt in den Berechnungsprozeß von präferenzierten Antwortmengen zu integrieren, so dass die bevorzugten Antwortmengen ohne Zwischenschritte berechnet werden können. Dazu entwickeln wir zuerst ein auf Graphen basierendes Gerüst zur Berechnung von Antwortmengen. Anschließend werden wir darin Präferenzen integrieren, so dass bevorzugte Antwortmengen ohne Compiler oder Meta-Interpretation berechnet werden. Es stellt sich heraus, dass die integrative Methode auf den meisten betrachteten Problemklassen wesentlich leistungsfähiger ist als der Compiler oder Meta-Interpretation. Ein weiterer Schwerpunkt dieser Arbeit liegt in der Frage, inwieweit sich geordnete logische Programme vereinfachen lassen. Dazu steht die Methodik der strengen Äquivalenz von logischen Programmen zur Verfügung. Wenn ein logisches Programm streng äquivalent zu einem seiner Teilprogramme ist, so kann man dieses durch das entsprechende Teilprogramm ersetzen, ohne dass sich die zugrunde liegende Semantik ändert. Bisher wurden strenge Äquivalenzen nicht für logische Programme mit Präferenzen untersucht. In dieser Arbeit definieren wir erstmalig strenge Äquivalenzen für geordnete logische Programme. Wir geben notwendige und hinreichende Bedingungen für die strenge Äquivalenz zweier geordneter logischer Programme an. Des Weiteren werden wir auch die Frage beantworten, inwieweit geordnete logische Programme und deren Präferenzstrukturen vereinfacht werden können. Abschließend präsentieren wir zwei neue Anwendungsbereiche von Präferenzen in der Antwortmengenprogrammierung. Zuerst definieren wir neue Prozeduren zur Entscheidungsfindung innerhalb von Gruppenprozessen. Diese integrieren wir anschließend in das Problem der Planung eines Treffens für eine Gruppe. Als zweite neue Anwendung rekonstruieren wir mit Hilfe der Antwortmengenprogrammierung eine linguistische Problemstellung, die in deutschen Dialekten auftritt. Momentan wird im Bereich der Linguistik darüber diskutiert, ob Regelsysteme von (menschlichen) Sprachen einzigartig sind oder nicht. Die Rekonstruktion von grammatikalischen Regularitäten mit Werkzeugen aus der Informatik erlaubt die Unterstützung der These, dass linguistische Regelsysteme Gemeinsamkeiten zu anderen nicht-linguistischen Regelsystemen besitzen. KW - Präferenzen KW - Antwortmengenprogrammierung KW - logische Programmierung KW - Künstliche Intelligenz KW - preferences KW - priorities KW - answer set programming KW - logic programming KW - artificial intelligence Y1 - 2007 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-12058 ER - TY - JOUR A1 - Gebser, Martin A1 - Obermeier, Philipp A1 - Schaub, Torsten 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 - Lindauer, Marius A1 - Hoos, Holger A1 - Leyton-Brown, Kevin A1 - Schaub, Torsten T1 - Automatic construction of parallel portfolios via algorithm configuration JF - Artificial intelligence N2 - Since 2004, increases in computational power described by Moore's law have substantially been realized in the form of additional cores rather than through faster clock speeds. To make effective use of modern hardware when solving hard computational problems, it is therefore necessary to employ parallel solution strategies. In this work, we demonstrate how effective parallel solvers for propositional satisfiability (SAT), one of the most widely studied NP-complete problems, can be produced automatically from any existing sequential, highly parametric SAT solver. Our Automatic Construction of Parallel Portfolios (ACPP) approach uses an automatic algorithm configuration procedure to identify a set of configurations that perform well when executed in parallel. Applied to two prominent SAT solvers, Lingeling and clasp, our ACPP procedure identified 8-core solvers that significantly outperformed their sequential counterparts on a diverse set of instances from the application and hard combinatorial category of the 2012 SAT Challenge. We further extended our ACPP approach to produce parallel portfolio solvers consisting of several different solvers by combining their configuration spaces. Applied to the component solvers of the 2012 SAT Challenge gold medal winning SAT Solver pfolioUZK, our ACPP procedures produced a significantly better-performing parallel SAT solver. KW - Algorithm configuration KW - Parallel SAT solving KW - Algorithm portfolios KW - Programming by optimization KW - Automated parallelization Y1 - 2016 U6 - https://doi.org/10.1016/j.artint.2016.05.004 SN - 0004-3702 SN - 1872-7921 VL - 244 SP - 272 EP - 290 PB - Elsevier CY - Amsterdam 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 - TY - JOUR A1 - Gebser, Martin A1 - Kaufmann, Benjamin A1 - Schaub, Torsten 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 - Besnard, Philippe A1 - Schaub, Torsten A1 - Tompits, Hans A1 - Woltran, Stefan T1 - Paraconsistent reasoning via quantified boolean formulas Y1 - 2002 SN - 3-540-44190-5 ER -