{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T07:33:58Z","timestamp":1723016038909},"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>How  can  we  plan  efficiently  in  a  large  and  complex environment when the time budget is limited? Given  the  original  simulator  of  the  environment, which may be computationally very demanding, we propose to learn online an approximate but much faster simulator that improves over time.  To plan reliably and efficiently while the approximate simulator is learning, we develop a method that adaptively decides which simulator to use for every simulation, based on a statistic that measures the accuracy of the approximate simulator. This allows us to use the approximate simulator to replace the original simulator for faster simulations when it is accurate enough under the current context, thus trading off  simulation speed  and  accuracy.   Experimental results in two large domains show that when integrated with POMCP, our approach allows to plan with improving efficiency over time.<\/jats:p>","DOI":"10.24963\/ijcai.2022\/642","type":"proceedings-article","created":{"date-parts":[[2022,7,16]],"date-time":"2022-07-16T02:55:56Z","timestamp":1657940156000},"page":"4628-4634","source":"Crossref","is-referenced-by-count":0,"title":["Online Planning in POMDPs with Self-Improving Simulators"],"prefix":"10.24963","author":[{"given":"Jinke","family":"He","sequence":"first","affiliation":[{"name":"Delft University of Technology"}]},{"given":"Miguel","family":"Suau","sequence":"additional","affiliation":[{"name":"Delft University of Technology"}]},{"given":"Hendrik","family":"Baier","sequence":"additional","affiliation":[{"name":"Centrum Wiskunde & Informatica"}]},{"given":"Michael","family":"Kaisers","sequence":"additional","affiliation":[{"name":"Centrum Wiskunde & Informatica"}]},{"given":"Frans A.","family":"Oliehoek","sequence":"additional","affiliation":[{"name":"Delft University of Technology"}]}],"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":"2022-07-18T11:10:51Z","timestamp":1658142651000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2022\/642"}},"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\/642","relation":{},"subject":[],"published":{"date-parts":[[2022,7]]}}}