{"type":"ScholarlyArticle","title":"Body-Decoupled Grounding via Solving: A Novel Approach on the ASP Bottleneck","authors":[{"name":"Viktor Besin","slug":"viktor-besin","given":"Viktor","family":"Besin","affiliation":"TU Wien , Vienna , Austria"},{"name":"Markus Hecher","slug":"markus-hecher","given":"Markus","family":"Hecher","affiliation":"TU Wien , Vienna , Austria; University of Potsdam , Potsdam , Germany"},{"name":"Stefan Woltran","slug":"stefan-woltran","given":"Stefan","family":"Woltran","affiliation":"TU Wien , Vienna , Austria"}],"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.","doi":"10.24963/ijcai.2022/353","url":"https://ijcai.org/proceedings/2022/353","pdf":"https://ijcai.org/proceedings/2022/0353.pdf","markdown":"https://ijcai.org/proceedings/2022/353.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/353","volume":{"slug":"2022","title":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2022","url":"https://ijcai.org/proceedings/2022/","year":2022,"location":"Vienna","dates":"23-29 July 2022","editors":"Luc De Raedt","isbn":"978-1-956792-00-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2022"},"section":"Knowledge Representation and Reasoning","track":"Main Track","number":353,"pages":{"first":2546,"last":2552},"keywords":["Knowledge Representation and Reasoning: Computational Complexity of Reasoning","Knowledge Representation and Reasoning: Logic Programming"],"videos":[{"label":"Video #1","url":"https://slideslive.com/38987113","length_sec":89,"provider":"slideslive"},{"label":"Video #2","url":"https://slideslive.com/38985256","length_sec":713,"provider":"slideslive"}],"references":[{"position":1,"raw":"[Alviano et al., 2019] Mario Alviano, Giovanni Amendola, Carmine Dodaro, Nicola Leone, Marco Maratea, and Francesco Ricca. 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