@article{GebserMarateaRicca2020, author = {Gebser, Martin and Maratea, Marco and Ricca, Francesco}, title = {The Seventh Answer Set Programming Competition}, series = {Theory and practice of logic programming}, volume = {20}, journal = {Theory and practice of logic programming}, number = {2}, publisher = {Cambridge Univ. Press}, address = {Cambridge [u.a.]}, issn = {1471-0684}, doi = {10.1017/S1471068419000061}, pages = {176 -- 204}, year = {2020}, abstract = {Answer Set Programming (ASP) is a prominent knowledge representation language with roots in logic programming and non-monotonic reasoning. Biennial ASP competitions are organized in order to furnish challenging benchmark collections and assess the advancement of the state of the art in ASP solving. In this paper, we report on the design and results of the Seventh ASP Competition, jointly organized by the University of Calabria (Italy), the University of Genova (Italy), and the University of Potsdam (Germany), in affiliation with the 14th International Conference on Logic Programming and Non-Monotonic Reasoning (LPNMR 2017).}, language = {en} } @article{CabalarFandinnoLierler2020, author = {Cabalar, Pedro and Fandinno, Jorge and Lierler, Yuliya}, title = {Modular Answer Set Programming as a formal specification language}, series = {Theory and practice of logic programming}, volume = {20}, journal = {Theory and practice of logic programming}, number = {5}, publisher = {Cambridge University Press}, address = {New York}, issn = {1471-0684}, doi = {10.1017/S1471068420000265}, pages = {767 -- 782}, year = {2020}, abstract = {In this paper, we study the problem of formal verification for Answer Set Programming (ASP), namely, obtaining aformal proofshowing that the answer sets of a given (non-ground) logic programPcorrectly correspond to the solutions to the problem encoded byP, regardless of the problem instance. To this aim, we use a formal specification language based on ASP modules, so that each module can be proved to capture some informal aspect of the problem in an isolated way. This specification language relies on a novel definition of (possibly nested, first order)program modulesthat may incorporate local hidden atoms at different levels. Then,verifyingthe logic programPamounts to prove some kind of equivalence betweenPand its modular specification.}, language = {en} } @article{CabalarFandinnoGareaetal.2020, author = {Cabalar, Pedro and Fandinno, Jorge and Garea, Javier and Romero, Javier and Schaub, Torsten H.}, title = {Eclingo}, series = {Theory and practice of logic programming}, volume = {20}, journal = {Theory and practice of logic programming}, number = {6}, publisher = {Cambridge Univ. Press}, address = {New York}, issn = {1471-0684}, doi = {10.1017/S1471068420000228}, pages = {834 -- 847}, year = {2020}, abstract = {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.}, language = {en} } @phdthesis{Kaminski2023, author = {Kaminski, Roland}, title = {Complex reasoning with answer set programming}, school = {Universit{\"a}t Potsdam}, pages = {301}, year = {2023}, abstract = {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.}, language = {en} } @phdthesis{Hecher2021, author = {Hecher, Markus}, title = {Advanced tools and methods for treewidth-based problem solving}, doi = {10.25932/publishup-51251}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-512519}, school = {Universit{\"a}t Potsdam}, pages = {xv, 184}, year = {2021}, abstract = {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.}, language = {en} } @misc{AguadoCabalarFandinnoetal.2019, author = {Aguado, Felicidad and Cabalar, Pedro and Fandinno, Jorge and Pearce, David and Perez, Gilberto and Vidal, Concepcion}, title = {Revisiting explicit negation in answer set programming}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1104}, issn = {1866-8372}, doi = {10.25932/publishup-46969}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-469697}, pages = {908 -- 924}, year = {2019}, abstract = {A common feature in Answer Set Programming is the use of a second negation, stronger than default negation and sometimes called explicit, strong or classical negation. This explicit negation is normally used in front of atoms, rather than allowing its use as a regular operator. In this paper we consider the arbitrary combination of explicit negation with nested expressions, as those defined by Lifschitz, Tang and Turner. We extend the concept of reduct for this new syntax and then prove that it can be captured by an extension of Equilibrium Logic with this second negation. We study some properties of this variant and compare to the already known combination of Equilibrium Logic with Nelson's strong negation.}, language = {en} } @article{CabalarFandinnoSchaubetal.2019, author = {Cabalar, Pedro and Fandinno, Jorge and Schaub, Torsten H. and Schellhorn, Sebastian}, title = {Gelfond-Zhang aggregates as propositional formulas}, series = {Artificial intelligence}, volume = {274}, journal = {Artificial intelligence}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0004-3702}, doi = {10.1016/j.artint.2018.10.007}, pages = {26 -- 43}, year = {2019}, abstract = {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.}, language = {en} } @article{OstrowskiPauleveSchaubetal.2016, author = {Ostrowski, Max and Pauleve, L. and Schaub, Torsten H. and Siegel, A. and Guziolowski, Carito}, title = {Boolean network identification from perturbation time series data combining dynamics abstraction and logic programming}, series = {Biosystems : journal of biological and information processing sciences}, volume = {149}, journal = {Biosystems : journal of biological and information processing sciences}, publisher = {Elsevier}, address = {Oxford}, issn = {0303-2647}, doi = {10.1016/j.biosystems.2016.07.009}, pages = {139 -- 153}, year = {2016}, abstract = {Boolean networks (and more general logic models) are useful frameworks to study signal transduction across multiple pathways. Logic models can be learned from a prior knowledge network structure and multiplex phosphoproteomics data. However, most efficient and scalable training methods focus on the comparison of two time-points and assume that the system has reached an early steady state. In this paper, we generalize such a learning procedure to take into account the time series traces of phosphoproteomics data in order to discriminate Boolean networks according to their transient dynamics. To that end, we identify a necessary condition that must be satisfied by the dynamics of a Boolean network to be consistent with a discretized time series trace. Based on this condition, we use Answer Set Programming to compute an over-approximation of the set of Boolean networks which fit best with experimental data and provide the corresponding encodings. Combined with model-checking approaches, we end up with a global learning algorithm. Our approach is able to learn logic models with a true positive rate higher than 78\% in two case studies of mammalian signaling networks; for a larger case study, our method provides optimal answers after 7 min of computation. We quantified the gain in our method predictions precision compared to learning approaches based on static data. Finally, as an application, our method proposes erroneous time-points in the time series data with respect to the optimal learned logic models. (C) 2016 Elsevier Ireland Ltd. All rights reserved.}, language = {en} } @article{GebserKaminskiSchaub2011, author = {Gebser, Martin and Kaminski, Roland and Schaub, Torsten H.}, title = {Complex optimization in answer set programming}, series = {Theory and practice of logic programming}, volume = {11}, journal = {Theory and practice of logic programming}, number = {3}, publisher = {Cambridge Univ. Press}, address = {New York}, issn = {1471-0684}, doi = {10.1017/S1471068411000329}, pages = {821 -- 839}, year = {2011}, abstract = {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.}, language = {en} } @article{MileoSchaubMericoetal.2011, author = {Mileo, Alessandra and Schaub, Torsten H. and Merico, Davide and Bisiani, Roberto}, title = {Knowledge-based multi-criteria optimization to support indoor positioning}, series = {Annals of mathematics and artificial intelligence}, volume = {62}, journal = {Annals of mathematics and artificial intelligence}, number = {3-4}, publisher = {Springer}, address = {Dordrecht}, issn = {1012-2443}, doi = {10.1007/s10472-011-9241-2}, pages = {345 -- 370}, year = {2011}, abstract = {Indoor position estimation constitutes a central task in home-based assisted living environments. Such environments often rely on a heterogeneous collection of low-cost sensors whose diversity and lack of precision has to be compensated by advanced techniques for localization and tracking. Although there are well established quantitative methods in robotics and neighboring fields for addressing these problems, they lack advanced knowledge representation and reasoning capacities. Such capabilities are not only useful in dealing with heterogeneous and incomplete information but moreover they allow for a better inclusion of semantic information and more general homecare and patient-related knowledge. We address this problem and investigate how state-of-the-art localization and tracking methods can be combined with Answer Set Programming, as a popular knowledge representation and reasoning formalism. We report upon a case-study and provide a first experimental evaluation of knowledge-based position estimation both in a simulated as well as in a real setting.}, language = {en} }