Besin, V., Hecher, M., & Woltran, S. (2022). Body-Decoupled Grounding via Solving: A Novel Approach on the ASP Bottleneck. In Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22) (pp. 2546–2552). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2022/353
Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22)
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Veranstaltungszeitraum:
23-Jul-2022 - 29-Jul-2022
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Veranstaltungsort:
Wien, Österreich
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Umfang:
7
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Verlag:
International Joint Conferences on Artificial Intelligence
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Peer Reviewed:
Ja
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Keywords:
Knowledge Representation and Reasoning: Logic Programming; Computational Complexity of Reasoning
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Abstract:
Answer-Set Programming (ASP) has seen tremendous progress over the last two decades and is nowadays successfully applied in many real-world domains. However, for certain types of problems, the well-known ASP grounding bottleneck still causes severe problems. This becomes virulent when grounding of rules, where the variables have to be replaced by constants, leads to a ground pro- gram that is too huge to be processed by the ASP solver. In this work, we tackle this problem by a novel method that decouples non-ground atoms in rules in order to delegate the evaluation of rule bodies to the solving process. Our procedure translates a non-ground normal program into a ground disjunctive program that is exponential only in the maximum predicate arity, and thus polynomial if this arity is assumed to be bounded by a constant. We demonstrate the feasibility of this new method experimentally by comparing it to standard ASP technology in terms of grounding size, grounding time and total runtime.
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Projekttitel:
Hybrid Parameterized Problem Solving in Practice: P32830-N (Fonds zur Förderung der wissenschaftlichen Forschung (FWF)) Revealing and Utilizing the Hidden Structure for Solving Hard Problems in AI: ICT19-065 (WWTF Wiener Wissenschafts-, Forschu und Technologiefonds)