{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T07:00:10Z","timestamp":1762326010426,"version":"build-2065373602"},"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":[[2025,11]]},"abstract":"<jats:p>The grounding bottleneck in Answer Set Programming prohibits large instances from being solved. This is caused by a combinatorial explosion in the grounding phase of standard ground&amp;solve systems. A promising alternative is Body-Decoupled Grounding (BDG), which grounds each body\n\npredicate on its own. However, BDG faces challenges in terms of worst-case grounding size and limited interoperability with other systems.\n\nThis paper addresses shortcomings of BDG by introducing FastFound: an alternative foundedness check that significantly reduces grounding sizes, by grounding each predicate on its own. FastFound\u2019s foundedness check is done implicitly, which leads to a quadratic reduction in grounding size. We start by introducing FastFound for tight normal rules, where we observe that this cannot be substantially improved. Then we extend FastFound to head-cycle-free programs and give novel interoperability\n\nresults for full disjunctive programs. An experimental evaluation on our prototype shows promising results, as we solve more grounding-heavy tasks than both standard ground&amp;solve systems and BDG.<\/jats:p>","DOI":"10.24963\/kr.2025\/10","type":"proceedings-article","created":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T06:10:44Z","timestamp":1762323044000},"page":"100-109","source":"Crossref","is-referenced-by-count":0,"title":["FastFound: Easing the ASP Bottleneck via Predicate-Decoupled Grounding"],"prefix":"10.24963","author":[{"given":"Alexander","family":"Beiser","sequence":"first","affiliation":[{"name":"TU Wien, Vienna, Austria"}]},{"given":"Martin","family":"Gebser","sequence":"additional","affiliation":[{"name":"University of Klagenfurt, Klagenfurt, Austria"}]},{"given":"Markus","family":"Hecher","sequence":"additional","affiliation":[{"name":"CNRS, Computer Science Research Center of Lens (CRIL), Univ. Artois, Lens, France"}]},{"given":"Stefan","family":"Woltran","sequence":"additional","affiliation":[{"name":"TU Wien, Vienna, Austria"}]}],"member":"10584","event":{"name":"22nd International Conference on Principles of Knowledge Representation and Reasoning {KR-2025}","theme":"Artificial Intelligence","location":"Melbourne, Australia","acronym":"KR-2025","number":"22","sponsor":["Artificial Intelligence Journal","Principles of Knowledge Representation and Reasoning Inc.","Academic College of Tel-Aviv","European Association for Artificial Intelligence","National Science Foundation"],"start":{"date-parts":[[2025,11,11]]},"end":{"date-parts":[[2025,11,17]]}},"container-title":["Proceedings of the TwentySecond International Conference on Principles of Knowledge Representation and Reasoning"],"original-title":[],"deposited":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T06:10:52Z","timestamp":1762323052000},"score":1,"resource":{"primary":{"URL":"https:\/\/proceedings.kr.org\/2025\/10"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2025,11]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/kr.2025\/10","relation":{},"subject":[],"published":{"date-parts":[[2025,11]]}}}