{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T03:05:08Z","timestamp":1767236708034},"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":[[2020,7]]},"abstract":"<jats:p>We consider optimal and anytime algorithms for the Euclidean Shortest Path Problem (ESPP) in two dimensions. Our approach leverages ideas from two recent works: Polyanya, a mesh-based ESPP planner which we use to represent and reason about the environment, and Compressed Path Databases, a speedup technique for pathfinding on grids and spatial networks, which we exploit to compute fast candidate paths. In a range of experiments and empirical comparisons we show that: (i) the auxiliary data structures required by the new method are cheap to build and store; (ii) for optimal search, the new algorithm is faster than a range of recent ESPP planners, with speedups ranging from several factors to over one order of magnitude; (iii) for anytime search, where feasible solutions are needed fast, we report even better runtimes.<\/jats:p>","DOI":"10.24963\/ijcai.2020\/584","type":"proceedings-article","created":{"date-parts":[[2020,7,8]],"date-time":"2020-07-08T12:12:10Z","timestamp":1594210330000},"page":"4229-4235","source":"Crossref","is-referenced-by-count":7,"title":["Euclidean Pathfinding with Compressed Path Databases"],"prefix":"10.24963","author":[{"given":"Bojie","family":"Shen","sequence":"first","affiliation":[{"name":"Monash University, Melbourne, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muhammad Aamir","family":"Cheema","sequence":"additional","affiliation":[{"name":"Monash University, Melbourne, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel","family":"Harabor","sequence":"additional","affiliation":[{"name":"Monash University, Melbourne, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter J.","family":"Stuckey","sequence":"additional","affiliation":[{"name":"Monash University, Melbourne, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"28","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-PRICAI-2020","name":"Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}","start":{"date-parts":[[2020,7,11]]},"theme":"Artificial Intelligence","location":"Yokohama, Japan","end":{"date-parts":[[2020,7,17]]}},"container-title":["Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2020,7,9]],"date-time":"2020-07-09T02:16:08Z","timestamp":1594260968000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2020\/584"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2020,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2020\/584","relation":{},"subject":[],"published":{"date-parts":[[2020,7]]}}}