@article{AngerGebserJanhunenetal.2006, author = {Anger, Christian and Gebser, Martin and Janhunen, Tomi and Schaub, Torsten H.}, title = {What's a head without a body?}, year = {2006}, language = {en} } @article{GebserMarateaRicca2017, author = {Gebser, Martin and Maratea, Marco and Ricca, Francesco}, title = {The sixth answer set programming competition}, series = {Journal of artificial intelligence research : JAIR}, volume = {60}, journal = {Journal of artificial intelligence research : JAIR}, publisher = {AI Access Found.}, address = {Marina del Rey}, issn = {1076-9757}, doi = {10.1613/jair.5373}, pages = {41 -- 95}, year = {2017}, abstract = {Answer Set Programming (ASP) is a well-known paradigm of declarative programming with roots in logic programming and non-monotonic reasoning. Similar to other closely related problemsolving technologies, such as SAT/SMT, QBF, Planning and Scheduling, advancements in ASP solving are assessed in competition events. In this paper, we report about the design and results of the Sixth ASP Competition, which was jointly organized by the University of Calabria (Italy), Aalto University (Finland), and the University of Genoa (Italy), in affiliation with the 13th International Conference on Logic Programming and Non-Monotonic Reasoning. This edition maintained some of the design decisions introduced in 2014, e.g., the conception of sub-tracks, the scoring scheme,and the adherence to a fixed modeling language in order to push the adoption of the ASP-Core-2 standard. On the other hand, it featured also some novelties, like a benchmark selection stage classifying instances according to their empirical hardness, and a "Marathon" track where the topperforming systems are given more time for solving hard benchmarks.}, language = {en} } @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{GebserKaminskiKaufmannetal.2018, author = {Gebser, Martin and Kaminski, Roland and Kaufmann, Benjamin and L{\"u}hne, Patrick and Obermeier, Philipp and Ostrowski, Max and Romero Davila, Javier and Schaub, Torsten H. and Schellhorn, Sebastian and Wanko, Philipp}, title = {The Potsdam Answer Set Solving Collection 5.0}, series = {K{\"u}nstliche Intelligenz}, volume = {32}, journal = {K{\"u}nstliche Intelligenz}, number = {2-3}, publisher = {Springer}, address = {Heidelberg}, issn = {0933-1875}, doi = {10.1007/s13218-018-0528-x}, pages = {181 -- 182}, year = {2018}, abstract = {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.}, language = {en} } @article{AngerGebserLinkeetal.2005, author = {Anger, Christian and Gebser, Martin and Linke, Thomas and Neumann, Andre and Schaub, Torsten H.}, title = {The nomore++ approach to answer set solving}, year = {2005}, language = {en} } @article{AngerGebserLinkeetal.2005, author = {Anger, Christian and Gebser, Martin and Linke, Thomas and Neumann, Andre and Schaub, Torsten H.}, title = {The nomore++ approach to answer set solving}, year = {2005}, language = {en} } @article{GebserLiuNamasivayametal.2007, author = {Gebser, Martin and Liu, Lengning and Namasivayam, Gayathri and Neumann, Andr{\´e} and Schaub, Torsten H. and Truszczynski, Miroslaw}, title = {The first answer set programming system competition}, isbn = {978-3-540- 72199-4}, year = {2007}, language = {en} } @article{GebserSchaub2013, author = {Gebser, Martin and Schaub, Torsten H.}, title = {Tableau calculi for logic programs under answer set semantics}, 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 = {10.1145/2480759.2480767}, pages = {40}, year = {2013}, abstract = {We introduce formal proof systems based on tableau methods for analyzing computations in Answer Set Programming (ASP). Our approach furnishes fine-grained instruments for characterizing operations as well as strategies of ASP solvers. The granularity is detailed enough to capture a variety of propagation and choice methods of algorithms used for ASP solving, also incorporating SAT-based and conflict-driven learning approaches to some extent. This provides us with a uniform setting for identifying and comparing fundamental properties of ASP solving approaches. In particular, we investigate their proof complexities and show that the run-times of best-case computations can vary exponentially between different existing ASP solvers. Apart from providing a framework for comparing ASP solving approaches, our characterizations also contribute to their understanding by pinning down the constitutive atomic operations. Furthermore, our framework is flexible enough to integrate new inference patterns, and so to study their relation to existing ones. To this end, we generalize our approach and provide an extensible basis aiming at a modular incorporation of additional language constructs. This is exemplified by augmenting our basic tableau methods with cardinality constraints and disjunctions.}, language = {en} } @article{GebserObermeierSchaubetal.2018, author = {Gebser, Martin and Obermeier, Philipp and Schaub, Torsten H. and Ratsch-Heitmann, Michel and Runge, Mario}, title = {Routing driverless transport vehicles in car assembly with answer set programming}, series = {Theory and practice of logic programming}, volume = {18}, journal = {Theory and practice of logic programming}, number = {3-4}, publisher = {Cambridge Univ. Press}, address = {New York}, issn = {1471-0684}, doi = {10.1017/S1471068418000182}, pages = {520 -- 534}, year = {2018}, abstract = {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.}, language = {en} } @phdthesis{Gebser2011, author = {Gebser, Martin}, title = {Proof theory and algorithms for answer set programming}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-55425}, school = {Universit{\"a}t Potsdam}, year = {2011}, abstract = {Answer Set Programming (ASP) is an emerging paradigm for declarative programming, in which a computational problem is specified by a logic program such that particular models, called answer sets, match solutions. ASP faces a growing range of applications, demanding for high-performance tools able to solve complex problems. ASP integrates ideas from a variety of neighboring fields. In particular, automated techniques to search for answer sets are inspired by Boolean Satisfiability (SAT) solving approaches. While the latter have firm proof-theoretic foundations, ASP lacks formal frameworks for characterizing and comparing solving methods. Furthermore, sophisticated search patterns of modern SAT solvers, successfully applied in areas like, e.g., model checking and verification, are not yet established in ASP solving. We address these deficiencies by, for one, providing proof-theoretic frameworks that allow for characterizing, comparing, and analyzing approaches to answer set computation. For another, we devise modern ASP solving algorithms that integrate and extend state-of-the-art techniques for Boolean constraint solving. We thus contribute to the understanding of existing ASP solving approaches and their interconnections as well as to their enhancement by incorporating sophisticated search patterns. The central idea of our approach is to identify atomic as well as composite constituents of a propositional logic program with Boolean variables. This enables us to describe fundamental inference steps, and to selectively combine them in proof-theoretic characterizations of various ASP solving methods. In particular, we show that different concepts of case analyses applied by existing ASP solvers implicate mutual exponential separations regarding their best-case complexities. We also develop a generic proof-theoretic framework amenable to language extensions, and we point out that exponential separations can likewise be obtained due to case analyses on them. We further exploit fundamental inference steps to derive Boolean constraints characterizing answer sets. They enable the conception of ASP solving algorithms including search patterns of modern SAT solvers, while also allowing for direct technology transfers between the areas of ASP and SAT solving. Beyond the search for one answer set of a logic program, we address the enumeration of answer sets and their projections to a subvocabulary, respectively. The algorithms we develop enable repetition-free enumeration in polynomial space without being intrusive, i.e., they do not necessitate any modifications of computations before an answer set is found. Our approach to ASP solving is implemented in clasp, a state-of-the-art Boolean constraint solver that has successfully participated in recent solver competitions. Although we do here not address the implementation techniques of clasp or all of its features, we present the principles of its success in the context of ASP solving.}, language = {en} }