{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T07:43:05Z","timestamp":1723016585671},"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>Several hierarchical planning systems feature a rich level of language features making them capable of expressing real-world problems. One such feature that's used by several current planning systems is causal links, which are used to track search progress. The formalism combining Hierarchical Task Network (HTN) planning with these links known from Partial Order Causal Link (POCL) planning is often referred to as hybrid planning. In this paper we study the computational complexity of such hybrid planning problems. More specifically, we provide missing membership results to existing hardness proofs and thereby provide tight complexity bounds for all known subclasses of hierarchical planning problems. We also re-visit and correct a result from the literature for plan verification showing that it remains NP-complete even in the absence of a task hierarchy.<\/jats:p>","DOI":"10.24963\/ijcai.2022\/638","type":"proceedings-article","created":{"date-parts":[[2022,7,16]],"date-time":"2022-07-16T02:55:56Z","timestamp":1657940156000},"page":"4597-4605","source":"Crossref","is-referenced-by-count":1,"title":["Tight Bounds for Hybrid Planning"],"prefix":"10.24963","author":[{"given":"Pascal","family":"Bercher","sequence":"first","affiliation":[{"name":"The Australian National University"}]},{"given":"Songtuan","family":"Lin","sequence":"additional","affiliation":[{"name":"The Australian National University"}]},{"given":"Ron","family":"Alford","sequence":"additional","affiliation":[{"name":"MITRE Coporation"}]}],"member":"10584","event":{"number":"31","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2022","name":"Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}","start":{"date-parts":[[2022,7,23]]},"theme":"Artificial Intelligence","location":"Vienna, Austria","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":"2022-07-18T11:10:50Z","timestamp":1658142650000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2022\/638"}},"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\/638","relation":{},"subject":[],"published":{"date-parts":[[2022,7]]}}}