{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T07:38:15Z","timestamp":1723016295157},"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":[[2021,9]]},"abstract":"<jats:p>Hierarchical task network (HTN) planning is a model-based approach to planning. The HTN domain model consists of tasks and methods to decompose them into subtasks until obtaining primitive tasks (actions). There are recent methods for verifying if a given action sequence is a valid HTN plan. However, if the plan is invalid, all existing verification methods only say so without explaining why the plan is invalid. In the paper, we propose a method that corrects a given action sequence to form a valid HTN plan by deleting the minimal number of actions. This plan correction explains what is wrong with a given action sequence concerning the HTN domain model.<\/jats:p>","DOI":"10.24963\/kr.2021\/10","type":"proceedings-article","created":{"date-parts":[[2021,10,11]],"date-time":"2021-10-11T16:45:56Z","timestamp":1633970756000},"page":"99-109","source":"Crossref","is-referenced-by-count":1,"title":["Correcting Hierarchical Plans by Action Deletion"],"prefix":"10.24963","author":[{"given":"Roman","family":"Bart\u00e1k","sequence":"first","affiliation":[{"name":"Charles University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simona","family":"Ondr\u010dkov\u00e1","sequence":"additional","affiliation":[{"name":"Charles University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gregor","family":"Behnke","sequence":"additional","affiliation":[{"name":"University of Freiburg"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pascal","family":"Bercher","sequence":"additional","affiliation":[{"name":"Australian National University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"18","sponsor":["Artificial Intelligence Journal","Principles of Knowledge Representation and Reasoning Inc.","Sea AI Lab","Potassco Solutions","European Association for Artificial Intelligence"],"acronym":"KR-2021","name":"18th International Conference on Principles of Knowledge Representation and Reasoning {KR-2021}","start":{"date-parts":[[2020,11,12]]},"theme":"Artificial Intelligence","location":"Hanoii, Vietnam","end":{"date-parts":[[2021,11,18]]}},"container-title":["Proceedings of the Eighteenth International Conference on Principles of Knowledge Representation and Reasoning"],"original-title":[],"deposited":{"date-parts":[[2021,10,11]],"date-time":"2021-10-11T16:46:02Z","timestamp":1633970762000},"score":1,"resource":{"primary":{"URL":"https:\/\/proceedings.kr.org\/2021\/10"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2021,9]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/kr.2021\/10","relation":{},"subject":[],"published":{"date-parts":[[2021,9]]}}}