{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T19:55:15Z","timestamp":1770753315221,"version":"3.50.0"},"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>Chasing multiple mobile targets with multiple agents is important in several applications, such as computer games and police chasing scenarios. Existing approaches can compute optimal policies. However, they have a limited scalability, as they implement expensive minimax searches. We introduce a sub-optimal but scalable approach that assigns individual agents to individual targets and that can dynamically re-compute such assignments. We provide a theoretical analysis, including upper bounds on the number of time steps required to solve an instance. In a detailed empirical evaluation on grid maps, our algorithm scales up very convincingly beyond the limits of previous methods. On small problems, where a comparison to a minimax approach is possible, the results demonstrate a good solution quality for our method.<\/jats:p>","DOI":"10.24963\/ijcai.2017\/624","type":"proceedings-article","created":{"date-parts":[[2017,7,28]],"date-time":"2017-07-28T09:14:07Z","timestamp":1501233247000},"page":"4470-4476","source":"Crossref","is-referenced-by-count":7,"title":["A Scalable Approach to Chasing Multiple Moving Targets with Multiple Agents"],"prefix":"10.24963","author":[{"given":"Fan","family":"Xie","sequence":"first","affiliation":[{"name":"Google Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adi","family":"Botea","sequence":"additional","affiliation":[{"name":"IBM Research, Ireland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Akihiro","family":"Kishimoto","sequence":"additional","affiliation":[{"name":"IBM Research, Ireland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"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":"2017-07-28T11:54:49Z","timestamp":1501242889000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2017\/624"}},"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\/624","relation":{},"subject":[],"published":{"date-parts":[[2017,8]]}}}