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  - 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  - 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  - GEN
A1  - Dworschak, Steve
A1  - Grell, Susanne
A1  - Nikiforova, Victoria J.
A1  - Schaub, Torsten H.
A1  - Selbig, Joachim
T1  - Modeling biological networks by action languages via answer set programming
T2  - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe
N2  - We describe an approach to modeling biological networks by action languages via answer set programming. To this end, we propose an action language for modeling biological networks, building on previous work by Baral et al. We introduce its syntax and semantics along with a translation into answer set programming, an efficient Boolean Constraint Programming Paradigm. Finally, we describe one of its applications, namely, the sulfur starvation response-pathway of the model plant Arabidopsis thaliana and sketch the functionality of our system and its usage.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 843 
KW  - biological network model
KW  - action language
KW  - answer set programming
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-429846
SN  - 1866-8372
IS  - 843
ER  - 
TY  - GEN
A1  - Fandinno, Jorge
T1  - Founded (auto)epistemic equilibrium logic satisfies epistemic splitting
T2  - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
N2  - In a recent line of research, two familiar concepts from logic programming semantics (unfounded sets and splitting) were extrapolated to the case of epistemic logic programs. The property of epistemic splitting provides a natural and modular way to understand programs without epistemic cycles but, surprisingly, was only fulfilled by Gelfond's original semantics (G91), among the many proposals in the literature. On the other hand, G91 may suffer from a kind of self-supported, unfounded derivations when epistemic cycles come into play. Recently, the absence of these derivations was also formalised as a property of epistemic semantics called foundedness. Moreover, a first semantics proved to satisfy foundedness was also proposed, the so-called Founded Autoepistemic Equilibrium Logic (FAEEL). In this paper, we prove that FAEEL also satisfies the epistemic splitting property something that, together with foundedness, was not fulfilled by any other approach up to date. To prove this result, we provide an alternative characterisation of FAEEL as a combination of G91 with a simpler logic we called Founded Epistemic Equilibrium Logic (FEEL), which is somehow an extrapolation of the stable model semantics to the modal logic S5.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1060 
KW  - answer set programming
KW  - epistemic specifications
KW  - epistemic logic programs
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-469685
SN  - 1866-8372
IS  - 1060
SP  - 671
EP  - 687
ER  - 
TY  - GEN
A1  - Fichte, Johannes Klaus
A1  - Truszczynski, Miroslaw
A1  - Woltran, Stefan
T1  - Dual-normal logic programs
BT  - the forgotten class
T2  - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
N2  - Disjunctive Answer Set Programming is a powerful declarative programming paradigm with complexity beyond NP. Identifying classes of programs for which the consistency problem is in NP is of interest from the theoretical standpoint and can potentially lead to improvements in the design of answer set programming solvers. One of such classes consists of dual-normal programs, where the number of positive body atoms in proper rules is at most one. Unlike other classes of programs, dual-normal programs have received little attention so far. In this paper we study this class. We relate dual-normal programs to propositional theories and to normal programs by presenting several inter-translations. With the translation from dual-normal to normal programs at hand, we introduce the novel class of body-cycle free programs, which are in many respects dual to head-cycle free programs. We establish the expressive power of dual-normal programs in terms of SE- and UE-models, and compare them to normal programs. We also discuss the complexity of deciding whether dual-normal programs are strongly and uniformly equivalent.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 585 
KW  - answer set programming
KW  - classes of logic programs
KW  - strong and uniform equivalence
KW  - propositional satisfiability
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-414490
SN  - 1866-8372
IS  - 585
ER  - 
TY  - GEN
A1  - Gebser, Martin
A1  - Schaub, Torsten H.
A1  - Thiele, Sven
A1  - Veber, Philippe
T1  - Detecting inconsistencies in large biological networks with answer set programming
T2  - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
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.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 561 
KW  - answer set programming
KW  - bioinformatics
KW  - consistency
KW  - diagnosis
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-412467
SN  - 1866-8372
IS  - 561
ER  - 
TY  - GEN
A1  - Gebser, Martin
A1  - Kaminski, Roland
A1  - Schaub, Torsten H.
T1  - Complex optimization in answer set programming
T2  - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
N2  - Preference handling and optimization are indispensable means for addressing nontrivial applications in Answer Set Programming (ASP). However, their implementation becomes difficult whenever they bring about a significant increase in computational complexity. As a consequence, existing ASP systems do not offer complex optimization capacities, supporting, for instance, inclusion-based minimization or Pareto efficiency. Rather, such complex criteria are typically addressed by resorting to dedicated modeling techniques, like saturation. Unlike the ease of common ASP modeling, however, these techniques are rather involved and hardly usable by ASP laymen. We address this problem by developing a general implementation technique by means of meta-prpogramming, thus reusing existing ASP systems to capture various forms of qualitative preferences among answer sets. In this way, complex preferences and optimization capacities become readily available for ASP applications.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 554 
KW  - answer set programming
KW  - preference handling
KW  - complex optimization
KW  - meta-programming
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-412436
SN  - 1866-8372
IS  - 554
ER  - 
TY  - GEN
A1  - Hoos, Holger
A1  - Kaminski, Roland
A1  - Lindauer, Marius
A1  - Schaub, Torsten H.
T1  - aspeed
BT  - solver scheduling via answer set programming
T2  - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
N2  - Although Boolean Constraint Technology has made tremendous progress over the last decade, the efficacy of state-of-the-art solvers is known to vary considerably across different types of problem instances, and is known to depend strongly on algorithm parameters. This problem was addressed by means of a simple, yet effective approach using handmade, uniform, and unordered schedules of multiple solvers in ppfolio, which showed very impressive performance in the 2011 Satisfiability Testing (SAT) Competition. Inspired by this, we take advantage of the modeling and solving capacities of Answer Set Programming (ASP) to automatically determine more refined, that is, nonuniform and ordered solver schedules from the existing benchmarking data. We begin by formulating the determination of such schedules as multi-criteria optimization problems and provide corresponding ASP encodings. The resulting encodings are easily customizable for different settings, and the computation of optimum schedules can mostly be done in the blink of an eye, even when dealing with large runtime data sets stemming from many solvers on hundreds to thousands of instances. Also, the fact that our approach can be customized easily enabled us to swiftly adapt it to generate parallel schedules for multi-processor machines.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 588 
KW  - algorithm schedules
KW  - answer set programming
KW  - portfolio-based solving
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-414743
SN  - 1866-8372
IS  - 588
ER  - 
TY  - GEN
A1  - Banbara, Mutsunori
A1  - Soh, Takehide
A1  - Tamura, Naoyuki
A1  - Inoue, Katsumi
A1  - Schaub, Torsten H.
T1  - Answer set programming as a modeling language for course timetabling
T2  - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe
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.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 594 
KW  - answer set programming
KW  - educational timetabling
KW  - course timetabling
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-415469
SN  - 1866-8372
IS  - 594
SP  - 783
EP  - 798
ER  -