{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,7]],"date-time":"2025-07-07T15:27:49Z","timestamp":1751902069694,"version":"3.37.3"},"reference-count":20,"publisher":"World Scientific Pub Co Pte Ltd","issue":"05","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Artif. Intell. Tools"],"published-print":{"date-parts":[[2017,10]]},"abstract":"<jats:p> Many Artificial Intelligence techniques have been developed for intelligent and autonomous systems to act and make rational decisions based on perceptions of the world state. Among these techniques, HTN (Hierarchical Task Network) planning is one of the most used in practice. HTN planning is based on expressive languages allowing to specify complex expert knowledge for real world domains. At the same time, many preprocessing techniques for classical planning were proposed to speed up the search. One of these technique, named grounding, consists in enumerating and instantiating all the possible actions from the planning problem descriptions. This technique has proven its effectiveness. Therefore, combining the expressiveness of HTN planning with the efficiency of the grounding preprocessing techniques used in classical planning is a very challenging issue. In this paper, we propose a generic algorithm to ground the domain representation for HTN planning. We show experimentally that grounding process improves the performances of state of the art HTN planners on a range of planning problems from the International Planning Competition (IPC). <\/jats:p>","DOI":"10.1142\/s0218213017600211","type":"journal-article","created":{"date-parts":[[2017,10,19]],"date-time":"2017-10-19T02:10:05Z","timestamp":1508379005000},"page":"1760021","source":"Crossref","is-referenced-by-count":5,"title":["Grounding of HTN Planning Domain"],"prefix":"10.1142","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9641-0036","authenticated-orcid":false,"given":"Abdeldjalil","family":"Ramoul","sequence":"first","affiliation":[{"name":"University Grenoble Alpes, LIG, F-38000 Grenoble, France"},{"name":"Cloud Temple, 215 Avenue Georges Clemenceau, 92024, Nanterre Cedex, France"}]},{"given":"Damien","family":"Pellier","sequence":"additional","affiliation":[{"name":"University Grenoble Alpes, LIG, F-38000 Grenoble, France"}]},{"given":"Humbert","family":"Fiorino","sequence":"additional","affiliation":[{"name":"University Grenoble Alpes, LIG, F-38000 Grenoble, France"}]},{"given":"Sylvie","family":"Pesty","sequence":"additional","affiliation":[{"name":"University Grenoble Alpes, LIG, F-38000 Grenoble, France"}]}],"member":"219","published-online":{"date-parts":[[2017,10,18]]},"reference":[{"key":"p_1","first-page":"1505","volume":"201","author":"Weser M.","journal-title":"IEEE"},{"key":"p_6","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-007-9049-y"},{"key":"p_9","first-page":"9","volume":"5","author":"Haslum P.","year":"2005","journal-title":"Artificial Intelligence Conference"},{"key":"p_10","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1613\/jair.1492","volume":"22","author":"Hoffmann J.","year":"2004","journal-title":"Artificial Intelligence Research"},{"key":"p_13","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-008-0203-4"},{"key":"p_16","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2012.08.001"},{"key":"p_22","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(91)90024-E"},{"key":"p_24","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(84)90053-5"},{"key":"p_28","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2015.02.002"},{"key":"p_30","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1613\/jair.1141","volume":"20","author":"Nau D. 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L.","journal-title":"Artificial Intelligence Commun."}],"container-title":["International Journal on Artificial Intelligence Tools"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218213017600211","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T23:27:13Z","timestamp":1565134033000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218213017600211"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,10]]},"references-count":20,"journal-issue":{"issue":"05","published-online":{"date-parts":[[2017,10,18]]},"published-print":{"date-parts":[[2017,10]]}},"alternative-id":["10.1142\/S0218213017600211"],"URL":"https:\/\/doi.org\/10.1142\/s0218213017600211","relation":{},"ISSN":["0218-2130","1793-6349"],"issn-type":[{"type":"print","value":"0218-2130"},{"type":"electronic","value":"1793-6349"}],"subject":[],"published":{"date-parts":[[2017,10]]}}}