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The sixth answer set programming competition

  • 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”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.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Martin GebserORCiDGND, Marco MarateaORCiD, Francesco RiccaORCiD
DOI:https://doi.org/10.1613/jair.5373
ISSN:1076-9757
ISSN:1943-5037
Titel des übergeordneten Werks (Englisch):Journal of artificial intelligence research : JAIR
Verlag:AI Access Found.
Verlagsort:Marina del Rey
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Datum der Erstveröffentlichung:13.09.2017
Erscheinungsjahr:2017
Datum der Freischaltung:19.09.2022
Band:60
Seitenanzahl:55
Erste Seite:41
Letzte Seite:95
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Informatik und Computational Science
DDC-Klassifikation:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 000 Informatik, Informationswissenschaft, allgemeine Werke
Peer Review:Referiert
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