{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T00:07:43Z","timestamp":1768435663395,"version":"3.49.0"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7]]},"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.24963\/ijcai.2022\/353","type":"proceedings-article","created":{"date-parts":[[2022,7,15]],"date-time":"2022-07-15T22:55:56Z","timestamp":1657925756000},"page":"2546-2552","source":"Crossref","is-referenced-by-count":4,"title":["Body-Decoupled Grounding via Solving: A Novel Approach on the ASP Bottleneck"],"prefix":"10.24963","author":[{"given":"Viktor","family":"Besin","sequence":"first","affiliation":[{"name":"TU Wien, Vienna, Austria"}]},{"given":"Markus","family":"Hecher","sequence":"additional","affiliation":[{"name":"TU Wien, Vienna, Austria"},{"name":"University of Potsdam, Potsdam, Germany"}]},{"given":"Stefan","family":"Woltran","sequence":"additional","affiliation":[{"name":"TU Wien, Vienna, Austria"}]}],"member":"10584","event":{"name":"Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}","theme":"Artificial Intelligence","location":"Vienna, Austria","acronym":"IJCAI-2022","number":"31","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2022,7,23]]},"end":{"date-parts":[[2022,7,29]]}},"container-title":["Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T07:09:15Z","timestamp":1658128155000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2022\/353"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2022,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2022\/353","relation":{},"subject":[],"published":{"date-parts":[[2022,7]]}}}