{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T01:46:59Z","timestamp":1792115219909,"version":"4.4.0"},"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":[[2017,8]]},"abstract":"<jats:p>Classical planning is concerned with problems where a goal needs to be reached\n\nfrom a known initial state by doing actions with deterministic, known effects.\n\nClassical planners, however, deal only with classical problems that can be\n\nexpressed in declarative planning languages such as STRIPS or PDDL. This\n\nprevents their use on problems that are not easy to model declaratively or\n\nwhose dynamics are given via simulations. Simulators do not provide a\n\ndeclarative representation of actions, but simply return successor states.\n\nThe question we address in this paper is: can a planner that has access to\n\nthe structure of states and goals only, approach the performance of planners\n\nthat also have access to the structure of actions expressed in PDDL?\n\nTo answer this, we develop domain-independent, black box planning algorithms\n\nthat completely ignore action structure, and show that they match the\n\nperformance of state-of-the-art classical planners on the standard planning\n\nbenchmarks. Effective black box algorithms open up new possibilities for\n\nmodeling and for expressing control knowledge, which we also illustrate.<\/jats:p>","DOI":"10.24963\/ijcai.2017\/600","type":"proceedings-article","created":{"date-parts":[[2017,7,28]],"date-time":"2017-07-28T09:14:07Z","timestamp":1501233247000},"page":"4294-4301","source":"Crossref","is-referenced-by-count":6,"title":["Purely Declarative Action Descriptions are Overrated: Classical Planning with Simulators"],"prefix":"10.24963","author":[{"given":"Guillem","family":"Franc\u00e8s","sequence":"first","affiliation":[{"name":"Universitat Pompeu Fabra"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miquel","family":"Ram\u00edrez","sequence":"additional","affiliation":[{"name":"The University of Melbourne, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nir","family":"Lipovetzky","sequence":"additional","affiliation":[{"name":"The University of Melbourne, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hector","family":"Geffner","sequence":"additional","affiliation":[{"name":"ICREA"},{"name":"Universitat Pompeu Fabra"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"Twenty-Sixth International Joint Conference on Artificial Intelligence","theme":"Artificial Intelligence","location":"Melbourne, Australia","acronym":"IJCAI-2017","number":"26","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)","University of Technology Sydney (UTS)","Australian Computer Society (ACS)"],"start":{"date-parts":[[2017,8,19]]},"end":{"date-parts":[[2017,8,26]]}},"container-title":["Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2017,7,28]],"date-time":"2017-07-28T11:54:43Z","timestamp":1501242883000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2017\/600"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2017,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2017\/600","relation":{},"subject":[],"published":{"date-parts":[[2017,8]]}}}