TY - JOUR A1 - Schaub, Torsten A1 - Thielscher, Michael T1 - Skeptical query-answering in constrained default logic Y1 - 1996 SN - 3-540-61313-7 ER - TY - JOUR A1 - Brüning, Stefan A1 - Schaub, Torsten T1 - A model-based approach to consistency-checking Y1 - 1996 SN - 3-540-61286-6 ER - TY - JOUR A1 - Besnard, Philippe A1 - Schaub, Torsten T1 - Circumscribing inconsistency Y1 - 1997 SN - 1-558-60480-4 SN - 1045-0823 ER - TY - JOUR A1 - Schaub, Torsten A1 - Brüning, Stefan T1 - Prolog technology for default reasoning Y1 - 1996 SN - 0-471-96809-9 ER - TY - JOUR A1 - Delgrande, James Patrick A1 - Schaub, Torsten T1 - Compiling specificity into approaches to nonmonotonic reasoning Y1 - 1997 SN - 0004-3702 ER - TY - JOUR A1 - Linke, Thomas A1 - Schaub, Torsten T1 - Towards a classification of default logic Y1 - 1997 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 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 - Hoos, Holger A1 - Kaminski, Roland A1 - Lindauer, Marius A1 - Schaub, Torsten 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 - JOUR A1 - Gebser, Martin A1 - Kaufmann, Benjamin A1 - Kaminski, Roland A1 - Ostrowski, Max A1 - Schaub, Torsten 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 - JOUR A1 - Cabalar, Pedro A1 - Fandiño, Jorge A1 - Schaub, Torsten A1 - Schellhorn, Sebastian T1 - Gelfond-Zhang aggregates as propositional formulas JF - Artificial intelligence N2 - Answer Set Programming (ASP) has become a popular and widespread paradigm for practical Knowledge Representation thanks to its expressiveness and the available enhancements of its input language. One of such enhancements is the use of aggregates, for which different semantic proposals have been made. In this paper, we show that any ASP aggregate interpreted under Gelfond and Zhang's (GZ) semantics can be replaced (under strong equivalence) by a propositional formula. Restricted to the original GZ syntax, the resulting formula is reducible to a disjunction of conjunctions of literals but the formulation is still applicable even when the syntax is extended to allow for arbitrary formulas (including nested aggregates) in the condition. Once GZ-aggregates are represented as formulas, we establish a formal comparison (in terms of the logic of Here-and-There) to Ferraris' (F) aggregates, which are defined by a different formula translation involving nested implications. In particular, we prove that if we replace an F-aggregate by a GZ-aggregate in a rule head, we do not lose answer sets (although more can be gained). This extends the previously known result that the opposite happens in rule bodies, i.e., replacing a GZ-aggregate by an F-aggregate in the body may yield more answer sets. Finally, we characterize a class of aggregates for which GZ- and F-semantics coincide. KW - Aggregates KW - Answer Set Programming Y1 - 2019 U6 - https://doi.org/10.1016/j.artint.2018.10.007 SN - 0004-3702 SN - 1872-7921 VL - 274 SP - 26 EP - 43 PB - Elsevier CY - Amsterdam ER - TY - THES A1 - Videla, Santiago T1 - Reasoning on the response of logical signaling networks with answer set programming T1 - Modellierung Logischer Signalnetzwerke mittels Antwortmengenprogrammierung N2 - Deciphering the functioning of biological networks is one of the central tasks in systems biology. In particular, signal transduction networks are crucial for the understanding of the cellular response to external and internal perturbations. Importantly, in order to cope with the complexity of these networks, mathematical and computational modeling is required. We propose a computational modeling framework in order to achieve more robust discoveries in the context of logical signaling networks. More precisely, we focus on modeling the response of logical signaling networks by means of automated reasoning using Answer Set Programming (ASP). ASP provides a declarative language for modeling various knowledge representation and reasoning problems. Moreover, available ASP solvers provide several reasoning modes for assessing the multitude of answer sets. Therefore, leveraging its rich modeling language and its highly efficient solving capacities, we use ASP to address three challenging problems in the context of logical signaling networks: learning of (Boolean) logical networks, experimental design, and identification of intervention strategies. Overall, the contribution of this thesis is three-fold. Firstly, we introduce a mathematical framework for characterizing and reasoning on the response of logical signaling networks. Secondly, we contribute to a growing list of successful applications of ASP in systems biology. Thirdly, we present a software providing a complete pipeline for automated reasoning on the response of logical signaling networks. N2 - Deciphering the functioning of biological networks is one of the central tasks in systems biology. In particular, signal transduction networks are crucial for the understanding of the cellular response to external and internal perturbations. Importantly, in order to cope with the complexity of these networks, mathematical and computational modeling is required. We propose a computational modeling framework in order to achieve more robust discoveries in the context of logical signaling networks. More precisely, we focus on modeling the response of logical signaling networks by means of automated reasoning using Answer Set Programming (ASP). ASP provides a declarative language for modeling various knowledge representation and reasoning problems. Moreover, available ASP solvers provide several reasoning modes for assessing the multitude of answer sets. Therefore, leveraging its rich modeling language and its highly efficient solving capacities, we use ASP to address three challenging problems in the context of logical signaling networks: learning of (Boolean) logical networks, experimental design, and identification of intervention strategies. Overall, the contribution of this thesis is three-fold. Firstly, we introduce a mathematical framework for characterizing and reasoning on the response of logical signaling networks. Secondly, we contribute to a growing list of successful applications of ASP in systems biology. Thirdly, we present a software providing a complete pipeline for automated reasoning on the response of logical signaling networks. KW - Systembiologie KW - logische Signalnetzwerke KW - Antwortmengenprogrammierung KW - systems biology KW - logical signaling networks KW - answer set programming Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-71890 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 - 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 - TY - JOUR A1 - Gebser, Martin A1 - Kaufmann, Benjamin A1 - Neumann, André A1 - Schaub, Torsten T1 - Clasp : a conflict-driven answer set solver Y1 - 2007 SN - 978-3-540- 72199-4 ER - TY - JOUR A1 - Brain, Martin A1 - Faber, Wolfgang A1 - Maratea, Marco A1 - Polleres, Axel A1 - Schaub, Torsten A1 - Schindlauer, Roman T1 - What should an ASP solver output? : a multiple position paper Y1 - 2007 ER - TY - JOUR A1 - Thielscher, Michael A1 - Schaub, Torsten T1 - Default reasoning by deductive planning Y1 - 1995 ER - TY - JOUR A1 - Banbara, Mutsunori A1 - Soh, Takehide A1 - Tamura, Naoyuki A1 - Inoue, Katsumi A1 - Schaub, Torsten T1 - Answer set programming as a modeling language for course timetabling JF - Theory and practice of logic programming N2 - The course timetabling problem can be generally defined as the task of assigning a number of lectures to a limited set of timeslots and rooms, subject to a given set of hard and soft constraints. The modeling language for course timetabling is required to be expressive enough to specify a wide variety of soft constraints and objective functions. Furthermore, the resulting encoding is required to be extensible for capturing new constraints and for switching them between hard and soft, and to be flexible enough to deal with different formulations. In this paper, we propose to make effective use of ASP as a modeling language for course timetabling. We show that our ASP-based approach can naturally satisfy the above requirements, through an ASP encoding of the curriculum-based course timetabling problem proposed in the third track of the second international timetabling competition (ITC-2007). Our encoding is compact and human-readable, since each constraint is individually expressed by either one or two rules. Each hard constraint is expressed by using integrity constraints and aggregates of ASP. Each soft constraint S is expressed by rules in which the head is the form of penalty (S, V, C), and a violation V and its penalty cost C are detected and calculated respectively in the body. We carried out experiments on four different benchmark sets with five different formulations. We succeeded either in improving the bounds or producing the same bounds for many combinations of problem instances and formulations, compared with the previous best known bounds. KW - answer set programming KW - educational timetabling KW - course timetabling Y1 - 2013 U6 - https://doi.org/10.1017/S1471068413000495 SN - 1471-0684 VL - 13 IS - 2 SP - 783 EP - 798 PB - Cambridge Univ. Press CY - New York ER - TY - JOUR A1 - Gebser, Martin A1 - Sabuncu, Orkunt A1 - Schaub, Torsten 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 - 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 - Delgrande, James Patrick A1 - Schaub, Torsten A1 - Tompits, Hans T1 - A Preference-Based Framework for Updating logic Programs : preliminary reports Y1 - 2006 UR - http://www.easychair.org/FLoC-06/PREFS-preproceedings.pdf ER - TY - JOUR A1 - Linke, Thomas A1 - Schaub, Torsten T1 - An approach to query-answering in Reiter's default logic and the underlying existence of extensions problem. Y1 - 1998 SN - 3-540-65141-1 ER - TY - THES A1 - Thiele, Sven T1 - Modeling biological systems with Answer Set Programming T1 - Modellierung biologischer Systeme mit Answer Set Programming N2 - Biology has made great progress in identifying and measuring the building blocks of life. The availability of high-throughput methods in molecular biology has dramatically accelerated the growth of biological knowledge for various organisms. The advancements in genomic, proteomic and metabolomic technologies allow for constructing complex models of biological systems. An increasing number of biological repositories is available on the web, incorporating thousands of biochemical reactions and genetic regulations. Systems Biology is a recent research trend in life science, which fosters a systemic view on biology. In Systems Biology one is interested in integrating the knowledge from all these different sources into models that capture the interaction of these entities. By studying these models one wants to understand the emerging properties of the whole system, such as robustness. However, both measurements as well as biological networks are prone to considerable incompleteness, heterogeneity and mutual inconsistency, which makes it highly non-trivial to draw biologically meaningful conclusions in an automated way. Therefore, we want to promote Answer Set Programming (ASP) as a tool for discrete modeling in Systems Biology. ASP is a declarative problem solving paradigm, in which a problem is encoded as a logic program such that its answer sets represent solutions to the problem. ASP has intrinsic features to cope with incompleteness, offers a rich modeling language and highly efficient solving technology. We present ASP solutions, for the analysis of genetic regulatory networks, determining consistency with observed measurements and identifying minimal causes for inconsistency. We extend this approach for computing minimal repairs on model and data that restore consistency. This method allows for predicting unobserved data even in case of inconsistency. Further, we present an ASP approach to metabolic network expansion. This approach exploits the easy characterization of reachability in ASP and its various reasoning methods, to explore the biosynthetic capabilities of metabolic reaction networks and generate hypotheses for extending the network. Finally, we present the BioASP library, a Python library which encapsulates our ASP solutions into the imperative programming paradigm. The library allows for an easy integration of ASP solution into system rich environments, as they exist in Systems Biology. N2 - In den letzten Jahren wurden große Fortschritte bei der Identifikation und Messung der Bausteine des Lebens gemacht. Die Verfügbarkeit von Hochdurchsatzverfahren in der Molekularbiology hat das Anwachsen unseres biologischen Wissens dramatisch beschleunigt. Durch die technische Fortschritte in Genomic, Proteomic und Metabolomic wurde die Konstruktion komplexer Modelle biologischer Systeme ermöglicht. Immer mehr biologische Datenbanken sind über das Internet verfügbar, sie enthalten tausende Daten biochemischer Reaktionen und genetischer Regulation. System Biologie ist ein junger Forschungszweig der Biologie, der versucht Biologische Systeme in ihrer Ganzheit zu erforschen. Dabei ist man daran interessiert möglichst viel Wissen aus den unterschiedlichsten Bereichen in ein Modell zu aggregieren, welches das Zusammenwirken der verschiedensten Komponenten nachbildet. Durch das Studium derartiger Modelle erhofft man sich ein Verständnis der aufbauenden Eigenschaften, wie zum Beispiel Robustheit, des Systems zu erlangen. Es stellt sich jedoch die Problematik, das sowohl die biologischen Modelle als auch die verfügbaren Messwerte, oft unvollständig, miteinander unvereinbar oder fehlerhaft sind. All dies macht es schwierig biologisch sinnvolle Schlussfolgerungen zu ziehen. Daher, möchten wir in dieser Arbeit Antwortmengen Programmierung (engl. Answer Set Programming; ASP) als Werkzeug zur diskreten Modellierung system biologischer Probleme vorschlagen. ASP verfügt über eingebaute Eigenschaften zum Umgang mit unvollständiger Information, eine reichhaltige Modellierungssprache und hocheffiziente Berechnungstechniken. Wir präsentieren ASP Lösungen zur Analyse von Netzwerken genetischer Regulierungen, zur Prüfung der Konsistenz mit gemessene Daten, und zur Identifikation von Gründen für Inkonsistenz. Diesen Ansatz erweitern wir um die Möglichkeit zur Berechnung minimaler Reparaturen an Modell und Daten, welche Konsistenz erzeugen. Mithilfe dieser Methode werden wir in die Lage versetzt, auch im Fall von Inkonsistenz, noch ungemessene Daten vorherzusagen. Weiterhin, präsentieren wir einen ASP Ansatz zur Analyse metabolischer Netzwerke. Bei diesem Ansatz, nutzen wir zum einen aus das sich Erreichbarkeit mit ASP leicht spezifizieren lässt und das ASP mehrere mächtige Methoden zur Schlussfolgerung bereitstellt, welche sich auch kombiniert lassen. Dadurch wird es möglich die Synthese Möglichkeiten eines Metabolischen Netzwerks zu erforschen und Hypothesen für Erweiterungen des metabolischen Netzwerks zu berechnen. Zu guter Letzt, präsentieren wir die BioASP Softwarebibliothek. Die BioASP-Bibliothek kapselt unsere ASP Lösungen in das imperative Programmierparadigma und vereinfacht eine Integration von ASP Lösungen in heterogene Betriebsumgebungen, wie sie in der System Biologie vorherrschen. KW - Antwortmengen Programmierung KW - System Biologie KW - Inkonsistenz KW - Unvollständigkeit KW - Reparatur KW - answer set programming KW - systems biology KW - inconsistency KW - incompleteness KW - repair Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-59383 ER - TY - JOUR A1 - Cabalar, Pedro A1 - Dieguez, Martin A1 - Schaub, Torsten A1 - Schuhmann, Anna T1 - Towards metric temporal answer set programming JF - Theory and practice of logic programming N2 - We elaborate upon the theoretical foundations of a metric temporal extension of Answer Set Programming. In analogy to previous extensions of ASP with constructs from Linear Temporal and Dynamic Logic, we accomplish this in the setting of the logic of Here-and-There and its non-monotonic extension, called Equilibrium Logic. More precisely, we develop our logic on the same semantic underpinnings as its predecessors and thus use a simple time domain of bounded time steps. This allows us to compare all variants in a uniform framework and ultimately combine them in a common implementation. Y1 - 2020 U6 - https://doi.org/10.1017/S1471068420000307 SN - 1471-0684 SN - 1475-3081 VL - 20 IS - 5 SP - 783 EP - 798 PB - Cambridge Univ. Press CY - Cambridge [u.a.] ER - TY - JOUR A1 - Pearce, David A1 - Sarsakov, Vladimir A1 - Schaub, Torsten 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 - Anger, Christian A1 - Gebser, Martin A1 - Janhunen, Tomi A1 - Schaub, Torsten T1 - What's a head without a body? Y1 - 2006 ER - TY - JOUR A1 - Mileo, Alessandra A1 - Schaub, Torsten T1 - Qualitative constraint enforcement in advanced policy specification Y1 - 2007 ER - TY - JOUR A1 - Banbara, Mutsunori A1 - Inoue, Katsumi A1 - Kaufmann, Benjamin A1 - Okimoto, Tenda A1 - Schaub, Torsten A1 - Soh, Takehide A1 - Tamura, Naoyuki A1 - Wanko, Philipp T1 - teaspoon BT - solving the curriculum-based course timetabling problems with answer set programming JF - Annals of operation research N2 - Answer Set Programming (ASP) is an approach to declarative problem solving, combining a rich yet simple modeling language with high performance solving capacities. We here develop an ASP-based approach to curriculum-based course timetabling (CB-CTT), one of the most widely studied course timetabling problems. The resulting teaspoon system reads a CB-CTT instance of a standard input format and converts it into a set of ASP facts. In turn, these facts are combined with a first-order encoding for CB-CTT solving, which can subsequently be solved by any off-the-shelf ASP systems. We establish the competitiveness of our approach by empirically contrasting it to the best known bounds obtained so far via dedicated implementations. Furthermore, we extend the teaspoon system to multi-objective course timetabling and consider minimal perturbation problems. KW - Educational timetabling KW - Course timetabling KW - Answer set programming KW - Multi-objective optimization KW - Minimal perturbation problems Y1 - 2018 U6 - https://doi.org/10.1007/s10479-018-2757-7 SN - 0254-5330 SN - 1572-9338 VL - 275 IS - 1 SP - 3 EP - 37 PB - Springer CY - Dordrecht ER - 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 - JOUR A1 - Haubelt, Christian A1 - Neubauer, Kai A1 - Schaub, Torsten A1 - Wanko, Philipp T1 - Design space exploration with answer set programming JF - Künstliche Intelligenz N2 - The aim of our project design space exploration with answer set programming is to develop a general framework based on Answer Set Programming (ASP) that finds valid solutions to the system design problem and simultaneously performs Design Space Exploration (DSE) to find the most favorable alternatives. We leverage recent developments in ASP solving that allow for tight integration of background theories to create a holistic framework for effective DSE. Y1 - 2018 U6 - https://doi.org/10.1007/s13218-018-0530-3 SN - 0933-1875 SN - 1610-1987 VL - 32 IS - 2-3 SP - 205 EP - 206 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 - Neubauer, Kai A1 - Haubelt, Christian A1 - Wanko, Philipp A1 - Schaub, Torsten T1 - Utilizing quad-trees for efficient design space exploration with partial assignment evaluation T2 - 2018 23rd Asia and South Pacific Design Automation Conference (ASP-DAC) N2 - Recently, it has been shown that constraint-based symbolic solving techniques offer an efficient way for deciding binding and routing options in order to obtain a feasible system level implementation. In combination with various background theories, a feasibility analysis of the resulting system may already be performed on partial solutions. That is, infeasible subsets of mapping and routing options can be pruned early in the decision process, which fastens the solving accordingly. However, allowing a proper design space exploration including multi-objective optimization also requires an efficient structure for storing and managing non-dominated solutions. In this work, we propose and study the usage of the Quad-Tree data structure in the context of partial assignment evaluation during system synthesis. Out experiments show that unnecessary dominance checks can be avoided, which indicates a preference of Quad-Trees over a commonly used list-based implementation for large combinatorial optimization problems. Y1 - 2018 SN - 978-1-5090-0602-1 U6 - https://doi.org/10.1109/ASPDAC.2018.8297362 SN - 2153-6961 SP - 434 EP - 439 PB - IEEE CY - New York ER - TY - GEN A1 - Schäpers, Björn A1 - Niemueller, Tim A1 - Lakemeyer, Gerhard A1 - Gebser, Martin A1 - Schaub, Torsten 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 - GEN A1 - Bosser, Anne-Gwenn A1 - Cabalar, Pedro A1 - Dieguez, Martin A1 - Schaub, Torsten T1 - Introducing temporal stable models for linear dynamic logic T2 - 16th International Conference on Principles of Knowledge Representation and Reasoning N2 - We propose a new temporal extension of the logic of Here-and-There (HT) and its equilibria obtained by combining it with dynamic logic over (linear) traces. Unlike previous temporal extensions of HT based on linear temporal logic, the dynamic logic features allow us to reason about the composition of actions. For instance, this can be used to exercise fine grained control when planning in robotics, as exemplified by GOLOG. In this paper, we lay the foundations of our approach, and refer to it as Linear Dynamic Equilibrium Logic, or simply DEL. We start by developing the formal framework of DEL and provide relevant characteristic results. Among them, we elaborate upon the relationships to traditional linear dynamic logic and previous temporal extensions of HT. Y1 - 2018 UR - https://www.dc.fi.udc.es/~cabalar/del.pdf SP - 12 EP - 21 PB - ASSOC Association for the Advancement of Artificial Intelligence CY - Palo Alto ER - TY - JOUR A1 - Cabalar, Pedro A1 - Fandiño, Jorge A1 - Garea, Javier A1 - Romero, Javier A1 - Schaub, Torsten T1 - Eclingo BT - a solver for epistemic logic programs JF - Theory and practice of logic programming N2 - We describe eclingo, a solver for epistemic logic programs under Gelfond 1991 semantics built upon the Answer Set Programming system clingo. The input language of eclingo uses the syntax extension capabilities of clingo to define subjective literals that, as usual in epistemic logic programs, allow for checking the truth of a regular literal in all or in some of the answer sets of a program. The eclingo solving process follows a guess and check strategy. It first generates potential truth values for subjective literals and, in a second step, it checks the obtained result with respect to the cautious and brave consequences of the program. This process is implemented using the multi-shot functionalities of clingo. We have also implemented some optimisations, aiming at reducing the search space and, therefore, increasing eclingo 's efficiency in some scenarios. Finally, we compare the efficiency of eclingo with two state-of-the-art solvers for epistemic logic programs on a pair of benchmark scenarios and show that eclingo generally outperforms their obtained results. KW - Answer Set Programming KW - Epistemic Logic Programs KW - Non-Monotonic KW - Reasoning KW - Conformant Planning Y1 - 2020 U6 - https://doi.org/10.1017/S1471068420000228 SN - 1471-0684 SN - 1475-3081 VL - 20 IS - 6 SP - 834 EP - 847 PB - Cambridge Univ. Press CY - New York ER - TY - THES A1 - Kaminski, Roland T1 - Complex reasoning with answer set programming N2 - Answer Set Programming (ASP) allows us to address knowledge-intensive search and optimization problems in a declarative way due to its integrated modeling, grounding, and solving workflow. A problem is modeled using a rule based language and then grounded and solved. Solving results in a set of stable models that correspond to solutions of the modeled problem. In this thesis, we present the design and implementation of the clingo system---perhaps, the most widely used ASP system. It features a rich modeling language originating from the field of knowledge representation and reasoning, efficient grounding algorithms based on database evaluation techniques, and high performance solving algorithms based on Boolean satisfiability (SAT) solving technology. The contributions of this thesis lie in the design of the modeling language, the design and implementation of the grounding algorithms, and the design and implementation of an Application Programmable Interface (API) facilitating the use of ASP in real world applications and the implementation of complex forms of reasoning beyond the traditional ASP workflow. KW - Answer Set Programming KW - Declarative Problem Solving KW - Grounding Theory KW - Preference Handling KW - Answer Set Solving modulo Theories KW - Temporal Answer Set Solving Y1 - 2023 ER - TY - THES A1 - Hecher, Markus T1 - Advanced tools and methods for treewidth-based problem solving N2 - In the last decades, there was a notable progress in solving the well-known Boolean satisfiability (Sat) problem, which can be witnessed by powerful Sat solvers. One of the reasons why these solvers are so fast are structural properties of instances that are utilized by the solver’s interna. This thesis deals with the well-studied structural property treewidth, which measures the closeness of an instance to being a tree. In fact, there are many problems parameterized by treewidth that are solvable in polynomial time in the instance size when parameterized by treewidth. In this work, we study advanced treewidth-based methods and tools for problems in knowledge representation and reasoning (KR). Thereby, we provide means to establish precise runtime results (upper bounds) for canonical problems relevant to KR. Then, we present a new type of problem reduction, which we call decomposition-guided (DG) that allows us to precisely monitor the treewidth when reducing from one problem to another problem. This new reduction type will be the basis for a long-open lower bound result for quantified Boolean formulas and allows us to design a new methodology for establishing runtime lower bounds for problems parameterized by treewidth. Finally, despite these lower bounds, we provide an efficient implementation of algorithms that adhere to treewidth. Our approach finds suitable abstractions of instances, which are subsequently refined in a recursive fashion, and it uses Sat solvers for solving subproblems. It turns out that our resulting solver is quite competitive for two canonical counting problems related to Sat. N2 - In den letzten Jahrzehnten konnte ein beachtlicher Fortschritt im Bereich der Aussagenlogik verzeichnet werden. Dieser äußerte sich dadurch, dass für das wichtigste Problem in diesem Bereich, genannt „Sat“, welches sich mit der Fragestellung befasst, ob eine gegebene aussagenlogische Formel erfüllbar ist oder nicht, überwältigend schnelle Computerprogramme („Solver“) entwickelt werden konnten. Interessanterweise liefern diese Solver eine beeindruckende Leistung, weil sie oft selbst Probleminstanzen mit mehreren Millionen von Variablen spielend leicht lösen können. Auf der anderen Seite jedoch glaubt man in der Wissenschaft weitgehend an die Exponentialzeithypothese (ETH), welche besagt, dass man im schlimmsten Fall für das Lösen einer Instanz in diesem Bereich exponentielle Laufzeit in der Anzahl der Variablen benötigt. Dieser vermeintliche Widerspruch ist noch immer nicht vollständig geklärt, denn wahrscheinlich gibt es viele ineinandergreifende Gründe für die Schnelligkeit aktueller Sat Solver. Einer dieser Gründe befasst sich weitgehend mit strukturellen Eigenschaften von Probleminstanzen, die wohl indirekt und intern von diesen Solvern ausgenützt werden. Diese Dissertation beschäftigt sich mit solchen strukturellen Eigenschaften, nämlich mit der sogenannten Baumweite. Die Baumweite ist sehr gut erforscht und versucht zu messen, wie groß der Abstand von Probleminstanzen zu Bäumen ist (Baumnähe). Allerdings ist dieser Parameter sehr generisch und bei Weitem nicht auf Problemstellungen der Aussagenlogik beschränkt. Tatsächlich gibt es viele weitere Probleme, die parametrisiert mit Baumweite in polynomieller Zeit gelöst werden können. Interessanterweise gibt es auch viele Probleme in der Wissensrepräsentation (KR), von denen man davon ausgeht, dass sie härter sind als das Problem Sat, die bei beschränkter Baumweite in polynomieller Zeit gelöst werden können. Ein prominentes Beispiel solcher Probleme ist das Problem QSat, welches sich für die Gültigkeit einer gegebenen quantifizierten, aussagenlogischen Formel (QBF), das sind aussagenlogische Formeln, wo gewisse Variablen existenziell bzw. universell quantifiziert werden können, befasst. Bemerkenswerterweise wird allerdings auch im Zusammenhang mit Baumweite, ähnlich zu Methoden der klassischen Komplexitätstheorie, die tatsächliche Komplexität (Härte) solcher Problemen quantifiziert, wo man die exakte Laufzeitabhängigkeit beim Problemlösen in der Baumweite (Stufe der Exponentialität) beschreibt. Diese Arbeit befasst sich mit fortgeschrittenen, Baumweite-basierenden Methoden und Werkzeugen für Probleme der Wissensrepräsentation und künstlichen Intelligenz (AI). Dabei präsentieren wir Methoden, um präzise Laufzeitresultate (obere Schranken) für prominente Fragmente der Antwortmengenprogrammierung (ASP), welche ein kanonisches Paradigma zum Lösen von Problemen der Wissensrepräsentation darstellt, zu erhalten. Unsere Resultate basieren auf dem Konzept der dynamischen Programmierung, die angeleitet durch eine sogenannte Baumzerlegung und ähnlich dem Prinzip „Teile-und-herrsche“ funktioniert. Solch eine Baumzerlegung ist eine konkrete, strukturelle Zerlegung einer Probleminstanz, die sich stark an der Baumweite orientiert. Des Weiteren präsentieren wir einen neuen Typ von Problemreduktion, den wir als „decomposition-guided (DG)“, also „zerlegungsangeleitet“, bezeichnen. Dieser Reduktionstyp erlaubt es, Baumweiteerhöhungen und -verringerungen während einer Problemreduktion von einem bestimmten Problem zu einem anderen Problem präzise zu untersuchen und zu kontrollieren. Zusätzlich ist dieser neue Reduktionstyp die Basis, um ein lange offen gebliebenes Resultat betreffend quantifizierter, aussagenlogischer Formeln zu zeigen. Tatsächlich sind wir damit in der Lage, präzise untere Schranken, unter der Annahme der Exponentialzeithypothese, für das Problem QSat bei beschränkter Baumweite zu zeigen. Genauer gesagt können wir mit diesem Konzept der DG Reduktionen zeigen, dass das Problem QSat, beschränkt auf Quantifizierungsrang ` und parametrisiert mit Baumweite k, im Allgemeinen nicht besser als in einer Laufzeit, die `-fach exponentiell in der Baumweite und polynomiell in der Instanzgröße ist1, lösen. Dieses Resultat hebt auf nicht-inkrementelle Weise ein bekanntes Ergebnis für Quantifizierungsrang 2 auf beliebige Quantifizierungsränge, allerdings impliziert es auch sehr viele weitere Konsequenzen. Das Resultat über die untere Schranke des Problems QSat erlaubt es, eine neue Methodologie zum Zeigen unterer Schranken einer Vielzahl von Problemen der Wissensrepräsentation und künstlichen Intelligenz, zu etablieren. In weiterer Konsequenz können wir damit auch zeigen, dass die oberen Schranken sowie die DG Reduktionen dieser Arbeit unter der Hypothese ETH „eng“ sind, d.h., sie können wahrscheinlich nicht mehr signifikant verbessert werden. Die Ergebnisse betreffend der unteren Schranken für QSat und die dazugehörige Methodologie konstituieren in gewisser Weise eine Hierarchie von über Baumweite parametrisierte Laufzeitklassen. Diese Laufzeitklassen können verwendet werden, um die Härte von Problemen für das Ausnützen von Baumweite zu quantifizieren und diese entsprechend ihrer Laufzeitabhängigkeit bezüglich Baumweite zu kategorisieren. Schlussendlich und trotz der genannten Resultate betreffend unterer Schranken sind wir im Stande, eine effiziente Implementierung von Algorithmen basierend auf dynamischer Programmierung, die entlang einer Baumzerlegung angeleitet wird, zur Verfügung zu stellen. Dabei funktioniert unser Ansatz dahingehend, indem er probiert, passende Abstraktionen von Instanzen zu finden, die dann im Endeffekt sukzessive und auf rekursive Art und Weise verfeinert und verbessert werden. Inspiriert durch die enorme Effizienz und Effektivität der Sat Solver, ist unsere Implementierung ein hybrider Ansatz, weil sie den starken Gebrauch von Sat Solvern zum Lösen diverser Subprobleme, die während der dynamischen Programmierung auftreten, pflegt. Dabei stellt sich heraus, dass der resultierende Solver unserer Implementierung im Bezug auf Effizienz beim Lösen von zwei kanonischen, Sat-verwandten Zählproblemen mit bestehenden Solvern locker mithalten kann. Tatsächlich sind wir im Stande, Instanzen, wo die oberen Schranken von Baumweite 260 übersteigen, zu lösen. Diese überraschende Beobachtung zeigt daher, dass Baumweite ein wichtiger Parameter sein könnte, der wohl in modernen Designs von Solvern berücksichtigt werden sollte. KW - Treewidth KW - Dynamic Programming KW - Knowledge Representation and Reasoning KW - Artificial Intelligence KW - Computational Complexity KW - Parameterized Complexity KW - Answer Set Programming KW - Exponential Time Hypothesis KW - Lower Bounds KW - Algorithms KW - Algorithmen KW - Antwortmengenprogrammierung KW - Künstliche Intelligenz KW - Komplexitätstheorie KW - Dynamische Programmierung KW - Exponentialzeit Hypothese KW - Wissensrepräsentation und Schlussfolgerung KW - Untere Schranken KW - Parametrisierte Komplexität KW - Baumweite Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-512519 ER - TY - JOUR A1 - Frioux, Clémence A1 - Schaub, Torsten A1 - Schellhorn, Sebastian A1 - Siegel, Anne A1 - Wanko, Philipp T1 - Hybrid metabolic network completion JF - Theory and practice of logic programming N2 - Metabolic networks play a crucial role in biology since they capture all chemical reactions in an organism. While there are networks of high quality for many model organisms, networks for less studied organisms are often of poor quality and suffer from incompleteness. To this end, we introduced in previous work an answer set programming (ASP)-based approach to metabolic network completion. Although this qualitative approach allows for restoring moderately degraded networks, it fails to restore highly degraded ones. This is because it ignores quantitative constraints capturing reaction rates. To address this problem, we propose a hybrid approach to metabolic network completion that integrates our qualitative ASP approach with quantitative means for capturing reaction rates. We begin by formally reconciling existing stoichiometric and topological approaches to network completion in a unified formalism. With it, we develop a hybrid ASP encoding and rely upon the theory reasoning capacities of the ASP system dingo for solving the resulting logic program with linear constraints over reals. We empirically evaluate our approach by means of the metabolic network of Escherichia coli. Our analysis shows that our novel approach yields greatly superior results than obtainable from purely qualitative or quantitative approaches. KW - answer set programming KW - metabolic network KW - gap-filling KW - linear programming KW - hybrid solving KW - bioinformatics Y1 - 2018 U6 - https://doi.org/10.1017/S1471068418000455 SN - 1471-0684 SN - 1475-3081 VL - 19 IS - 1 SP - 83 EP - 108 PB - Cambridge University Press CY - New York ER - TY - GEN A1 - Cabalar, Pedro A1 - Fandiño, Jorge A1 - Schaub, Torsten A1 - Schellhorn, Sebastian T1 - Lower Bound Founded Logic of Here-and-There T2 - Logics in Artificial Intelligence N2 - A distinguishing feature of Answer Set Programming is that all atoms belonging to a stable model must be founded. That is, an atom must not only be true but provably true. This can be made precise by means of the constructive logic of Here-and-There, whose equilibrium models correspond to stable models. One way of looking at foundedness is to regard Boolean truth values as ordered by letting true be greater than false. Then, each Boolean variable takes the smallest truth value that can be proven for it. This idea was generalized by Aziz to ordered domains and applied to constraint satisfaction problems. As before, the idea is that a, say integer, variable gets only assigned to the smallest integer that can be justified. In this paper, we present a logical reconstruction of Aziz’ idea in the setting of the logic of Here-and-There. More precisely, we start by defining the logic of Here-and-There with lower bound founded variables along with its equilibrium models and elaborate upon its formal properties. Finally, we compare our approach with related ones and sketch future work. Y1 - 2019 SN - 978-3-030-19570-0 SN - 978-3-030-19569-4 U6 - https://doi.org/10.1007/978-3-030-19570-0_34 SN - 0302-9743 SN - 1611-3349 VL - 11468 SP - 509 EP - 525 PB - Springer CY - Cham ER -