{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T10:06:23Z","timestamp":1767261983420},"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":[[2023,8]]},"abstract":"<jats:p>Planning tasks succinctly represent labeled transition systems, with each ground action corresponding to a label. This granularity, however, is not necessary for solving planning tasks and can be harmful, especially for model-free methods. In order to apply such methods, the label sets are often manually reduced. In this work, we propose automating this manual process. We characterize a valid label reduction for classical planning tasks and propose an automated way of obtaining such valid reductions by leveraging lifted mutex groups. Our experiments show a significant reduction in the action label space size across a wide collection of planning domains. We demonstrate the benefit of our automated label reduction in two separate use cases: improved sample complexity of model-free reinforcement learning algorithms and speeding up successor generation in lifted planning. The code and supplementary material are available at https:\/\/github.com\/IBM\/Parameter-Seed-Set.<\/jats:p>","DOI":"10.24963\/ijcai.2023\/599","type":"proceedings-article","created":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T08:31:30Z","timestamp":1691742690000},"page":"5394-5401","source":"Crossref","is-referenced-by-count":1,"title":["Action Space Reduction for Planning Domains"],"prefix":"10.24963","author":[{"given":"Harsha","family":"Kokel","sequence":"first","affiliation":[{"name":"IBM T.J. Watson Research Center, Yorktown Heights, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junkyu","family":"Lee","sequence":"additional","affiliation":[{"name":"IBM T.J. Watson Research Center, Yorktown Heights, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Katz","sequence":"additional","affiliation":[{"name":"IBM T.J. Watson Research Center, Yorktown Heights, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kavitha","family":"Srinivas","sequence":"additional","affiliation":[{"name":"IBM T.J. Watson Research Center, Yorktown Heights, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shirin","family":"Sohrabi","sequence":"additional","affiliation":[{"name":"IBM T.J. Watson Research Center, Yorktown Heights, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"32","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2023","name":"Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}","start":{"date-parts":[[2023,8,19]]},"theme":"Artificial Intelligence","location":"Macau, SAR China","end":{"date-parts":[[2023,8,25]]}},"container-title":["Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T08:52:10Z","timestamp":1691743930000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2023\/599"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2023,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2023\/599","relation":{},"subject":[],"published":{"date-parts":[[2023,8]]}}}