{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T13:13:17Z","timestamp":1762607597711},"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":[[2019,8]]},"abstract":"<jats:p>Compressed Path Databases (CPDs) are a leading technique for optimal pathfinding in graphs with static edge costs.  In this work we investigate CPDs as admissible heuristic functions and we apply them in two distinct settings: problems where the graph is subject to dynamically changing costs, and anytime settings where deliberation time is limited.  Conventional heuristics derive cost-to-go estimates by reasoning about a tentative and usually infeasible path, from the current node to the target.  CPD-based heuristics derive cost-to-go estimates by computing a concrete and usually feasible path.  We exploit such paths to bound the optimal solution, not just from below but also from above.  We demonstrate the benefit of this approach in a range of experiments on standard gridmaps and in comparison to Landmarks, a popular alternative also developed for searching in explicit state-spaces.<\/jats:p>","DOI":"10.24963\/ijcai.2019\/167","type":"proceedings-article","created":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T07:46:05Z","timestamp":1564299965000},"page":"1199-1205","source":"Crossref","is-referenced-by-count":4,"title":["Path Planning with CPD Heuristics"],"prefix":"10.24963","author":[{"given":"Massimo","family":"Bono","sequence":"first","affiliation":[{"name":"Dipartimento di Ingegneria dell\u2019Informazione, Universita degli Studi di Brescia, Brescia, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alfonso E.","family":"Gerevini","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria dell\u2019Informazione, Universita degli Studi di Brescia, Brescia, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel D.","family":"Harabor","sequence":"additional","affiliation":[{"name":"Faculty of Information Technology, Monash University, Melbourne, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter J.","family":"Stuckey","sequence":"additional","affiliation":[{"name":"Faculty of Information Technology, 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-2019","name":"Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}","start":{"date-parts":[[2019,8,10]]},"theme":"Artificial Intelligence","location":"Macao, China","end":{"date-parts":[[2019,8,16]]}},"container-title":["Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T07:47:16Z","timestamp":1564300036000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2019\/167"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2019,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2019\/167","relation":{},"subject":[],"published":{"date-parts":[[2019,8]]}}}