@article{GebserKaufmannKaminskietal.2011, author = {Gebser, Martin and Kaufmann, Benjamin and Kaminski, Roland and Ostrowski, Max and Schaub, Torsten H. and Schneider, Marius}, title = {Potassco the Potsdam answer set solving collection}, series = {AI communications : AICOM ; the European journal on artificial intelligence}, volume = {24}, journal = {AI communications : AICOM ; the European journal on artificial intelligence}, number = {2}, publisher = {IOS Press}, address = {Amsterdam}, issn = {0921-7126}, doi = {10.3233/AIC-2011-0491}, pages = {107 -- 124}, year = {2011}, abstract = {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.}, language = {en} } @article{GebserKaufmannSchaub2012, author = {Gebser, Martin and Kaufmann, Benjamin and Schaub, Torsten H.}, title = {Conflict-driven answer set solving: From theory to practice}, series = {Artificial intelligence}, volume = {187}, journal = {Artificial intelligence}, number = {8}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0004-3702}, doi = {10.1016/j.artint.2012.04.001}, pages = {52 -- 89}, year = {2012}, abstract = {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.}, language = {en} } @article{DelgrandeSchaubTompitsetal.2013, author = {Delgrande, James and Schaub, Torsten H. and Tompits, Hans and Woltran, Stefan}, title = {A model-theoretic approach to belief change in answer set programming}, series = {ACM transactions on computational logic}, volume = {14}, journal = {ACM transactions on computational logic}, number = {2}, publisher = {Association for Computing Machinery}, address = {New York}, issn = {1529-3785}, doi = {10.1145/2480759.2480766}, pages = {46}, year = {2013}, abstract = {We address the problem of belief change in (nonmonotonic) logic programming under answer set semantics. Our formal techniques are analogous to those of distance-based belief revision in propositional logic. In particular, we build upon the model theory of logic programs furnished by SE interpretations, where an SE interpretation is a model of a logic program in the same way that a classical interpretation is a model of a propositional formula. Hence we extend techniques from the area of belief revision based on distance between models to belief change in logic programs. We first consider belief revision: for logic programs P and Q, the goal is to determine a program R that corresponds to the revision of P by Q, denoted P * Q. We investigate several operators, including (logic program) expansion and two revision operators based on the distance between the SE models of logic programs. It proves to be the case that expansion is an interesting operator in its own right, unlike in classical belief revision where it is relatively uninteresting. Expansion and revision are shown to satisfy a suite of interesting properties; in particular, our revision operators satisfy all or nearly all of the AGM postulates for revision. We next consider approaches for merging a set of logic programs, P-1,...,P-n. Again, our formal techniques are based on notions of relative distance between the SE models of the logic programs. Two approaches are examined. The first informally selects for each program P-i those models of P-i that vary the least from models of the other programs. The second approach informally selects those models of a program P-0 that are closest to the models of programs P-1,...,P-n. In this case, P-0 can be thought of as a set of database integrity constraints. We examine these operators with regards to how they satisfy relevant postulate sets. Last, we present encodings for computing the revision as well as the merging of logic programs within the same logic programming framework. This gives rise to a direct implementation of our approach in terms of off-the-shelf answer set solvers. These encodings also reflect the fact that our change operators do not increase the complexity of the base formalism.}, language = {en} } @article{VidelaGuziolowskiEduatietal.2015, author = {Videla, Santiago and Guziolowski, Carito and Eduati, Federica and Thiele, Sven and Gebser, Martin and Nicolas, Jacques and Saez-Rodriguez, Julio and Schaub, Torsten H. and Siegel, Anne}, title = {Learning Boolean logic models of signaling networks with ASP}, series = {Theoretical computer science}, volume = {599}, journal = {Theoretical computer science}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0304-3975}, doi = {10.1016/j.tcs.2014.06.022}, pages = {79 -- 101}, year = {2015}, abstract = {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.}, language = {en} } @article{FichteSzeider2015, author = {Fichte, Johannes Klaus and Szeider, Stefan}, title = {Backdoors to tractable answer set programming}, series = {Artificial intelligence}, volume = {220}, journal = {Artificial intelligence}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0004-3702}, doi = {10.1016/j.artint.2014.12.001}, pages = {64 -- 103}, year = {2015}, abstract = {Answer Set Programming (ASP) is an increasingly popular framework for declarative programming that admits the description of problems by means of rules and constraints that form a disjunctive logic program. In particular, many Al problems such as reasoning in a nonmonotonic setting can be directly formulated in ASP. Although the main problems of ASP are of high computational complexity, complete for the second level of the Polynomial Hierarchy, several restrictions of ASP have been identified in the literature, under which ASP problems become tractable. In this paper we use the concept of backdoors to identify new restrictions that make ASP problems tractable. Small backdoors are sets of atoms that represent "clever reasoning shortcuts" through the search space and represent a hidden structure in the problem input. The concept of backdoors is widely used in theoretical investigations in the areas of propositional satisfiability and constraint satisfaction. We show that it can be fruitfully adapted to ASP. We demonstrate how backdoors can serve as a unifying framework that accommodates several tractable restrictions of ASP known from the literature. Furthermore, we show how backdoors allow us to deploy recent algorithmic results from parameterized complexity theory to the domain of answer set programming. (C) 2015 Elsevier B.V. All rights reserved.}, language = {en} } @article{BanbaraInoueKaufmannetal.2018, author = {Banbara, Mutsunori and Inoue, Katsumi and Kaufmann, Benjamin and Okimoto, Tenda and Schaub, Torsten H. and Soh, Takehide and Tamura, Naoyuki and Wanko, Philipp}, title = {teaspoon}, series = {Annals of operation research}, volume = {275}, journal = {Annals of operation research}, number = {1}, publisher = {Springer}, address = {Dordrecht}, issn = {0254-5330}, doi = {10.1007/s10479-018-2757-7}, pages = {3 -- 37}, year = {2018}, abstract = {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.}, language = {en} } @article{AguadoCabalarFandinoetal.2019, author = {Aguado, Felicidad and Cabalar, Pedro and Fandi{\~n}o, Jorge and Pearce, David and Perez, Gilberto and Vidal-Peracho, Concepcion}, title = {Revisiting Explicit Negation in Answer Set Programming}, series = {Theory and practice of logic programming}, volume = {19}, journal = {Theory and practice of logic programming}, number = {5-6}, publisher = {Cambridge Univ. Press}, address = {New York}, issn = {1471-0684}, doi = {10.1017/S1471068419000267}, pages = {908 -- 924}, year = {2019}, language = {en} } @article{AguadoCabalarFandinnoetal.2019, author = {Aguado, Felicidad and Cabalar, Pedro and Fandinno, Jorge and Pearce, David and Perez, Gilberto and Vidal, Concepcion}, title = {Forgetting auxiliary atoms in forks}, series = {Artificial intelligence}, volume = {275}, journal = {Artificial intelligence}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0004-3702}, doi = {10.1016/j.artint.2019.07.005}, pages = {575 -- 601}, year = {2019}, abstract = {In this work we tackle the problem of checking strong equivalence of logic programs that may contain local auxiliary atoms, to be removed from their stable models and to be forbidden in any external context. We call this property projective strong equivalence (PSE). It has been recently proved that not any logic program containing auxiliary atoms can be reformulated, under PSE, as another logic program or formula without them - this is known as strongly persistent forgetting. In this paper, we introduce a conservative extension of Equilibrium Logic and its monotonic basis, the logic of Here-and-There, in which we deal with a new connective '|' we call fork. We provide a semantic characterisation of PSE for forks and use it to show that, in this extension, it is always possible to forget auxiliary atoms under strong persistence. We further define when the obtained fork is representable as a regular formula.}, language = {en} } @article{Hecher2022, author = {Hecher, Markus}, title = {Treewidth-aware reductions of normal ASP to SAT}, series = {Artificial intelligence}, volume = {304}, journal = {Artificial intelligence}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0004-3702}, doi = {10.1016/j.artint.2021.103651}, pages = {24}, year = {2022}, abstract = {Answer Set Programming (ASP) is a paradigm for modeling and solving problems for knowledge representation and reasoning. There are plenty of results dedicated to studying the hardness of (fragments of) ASP. So far, these studies resulted in characterizations in terms of computational complexity as well as in fine-grained insights presented in form of dichotomy-style results, lower bounds when translating to other formalisms like propositional satisfiability (SAT), and even detailed parameterized complexity landscapes. A generic parameter in parameterized complexity originating from graph theory is the socalled treewidth, which in a sense captures structural density of a program. Recently, there was an increase in the number of treewidth-based solvers related to SAT. While there are translations from (normal) ASP to SAT, no reduction that preserves treewidth or at least keeps track of the treewidth increase is known. In this paper we propose a novel reduction from normal ASP to SAT that is aware of the treewidth, and guarantees that a slight increase of treewidth is indeed sufficient. Further, we show a new result establishing that, when considering treewidth, already the fragment of normal ASP is slightly harder than SAT (under reasonable assumptions in computational complexity). This also confirms that our reduction probably cannot be significantly improved and that the slight increase of treewidth is unavoidable. Finally, we present an empirical study of our novel reduction from normal ASP to SAT, where we compare treewidth upper bounds that are obtained via known decomposition heuristics. Overall, our reduction works better with these heuristics than existing translations. (c) 2021 Elsevier B.V. All rights reserved.}, language = {en} } @article{BreitenreiterAndjelkovićSchrapeetal.2022, author = {Breitenreiter, Anselm and Andjelković, Marko and Schrape, Oliver and Krstić, Miloš}, title = {Fast error propagation probability estimates by answer set programming and approximate model counting}, series = {IEEE Access}, volume = {10}, journal = {IEEE Access}, publisher = {Inst. of Electr. and Electronics Engineers}, address = {Piscataway}, issn = {2169-3536}, doi = {10.1109/ACCESS.2022.3174564}, pages = {51814 -- 51825}, year = {2022}, abstract = {We present a method employing Answer Set Programming in combination with Approximate Model Counting for fast and accurate calculation of error propagation probabilities in digital circuits. By an efficient problem encoding, we achieve an input data format similar to a Verilog netlist so that extensive preprocessing is avoided. By a tight interconnection of our application with the underlying solver, we avoid iterating over fault sites and reduce calls to the solver. Several circuits were analyzed with varying numbers of considered cycles and different degrees of approximation. Our experiments show, that the runtime can be reduced by approximation by a factor of 91, whereas the error compared to the exact result is below 1\%.}, language = {en} }