{"type":"ScholarlyArticle","title":"Extended Increasing Cost Tree Search for Non-Unit Cost Domains","authors":[{"name":"Thayne T. Walker","slug":"thayne-t-walker","given":"Thayne T.","family":"Walker","affiliation":"University of Denver , Denver , CO , USA"},{"name":"Nathan R. Sturtevant","slug":"nathan-r-sturtevant","given":"Nathan R.","family":"Sturtevant","affiliation":"University of Denver , Denver , CO , USA"},{"name":"Ariel Felner","slug":"ariel-felner","given":"Ariel","family":"Felner","affiliation":"Ben-Gurion University , Be'er-Sheva , Israel"}],"abstract":"Multi-agent pathfinding (MAPF) has applications\r\nin navigation, robotics, games and planning. Most\r\nwork on search-based optimal algorithms for\r\nMAPF has focused on simple domains with unit\r\ncost actions and unit time steps. Although these\r\nconstraints keep many aspects of the algorithms\r\nsimple, they also severely limit the domains that\r\ncan be used. In this paper we introduce a new definition\r\nof the MAPF problem for non-unit cost and\r\nnon-unit time step domains along with new multiagent\r\nstate successor generation schemes for these\r\ndomains. Finally, we define an extended version\r\nof the increasing cost tree search algorithm (ICTS)\r\nfor non-unit costs, with two new sub-optimal variants\r\nof ICTS: epsilon-ICTS and w-ICTS. Our experiments\r\nshow that higher quality sub-optimal solutions\r\nare achievable in domains with finely discretized\r\nmovement models in no more time than\r\nlower-quality, optimal solutions in domains with\r\ncoarsely discretized movement models.","doi":"10.24963/ijcai.2018/74","url":"https://ijcai.org/proceedings/2018/74","pdf":"https://ijcai.org/proceedings/2018/0074.pdf","markdown":"https://ijcai.org/proceedings/2018/74.md","bibtex":"https://ijcai.org/proceedings/2018/bibtex/74","volume":{"slug":"2018","title":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2018","url":"https://ijcai.org/proceedings/2018/","year":2018,"location":"Stockholm","dates":"13-19 July 2018","editors":"Jérôme Lang","isbn":"978-0-9992411-2-7","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2018"},"section":"Agent-based and Multi-agent Systems","track":"Main track","number":74,"pages":{"first":534,"last":540},"keywords":["Heuristic Search and Game Playing: Heuristic Search","Agent-based and Multi-agent Systems: Coordination and Cooperation","Robotics: Multi-Robot Systems","Agent-based and Multi-agent Systems: Multi-agent Planning","Planning and Scheduling: Distributed;Multi-agent Planning","Heuristic Search and Game Playing: Combinatorial Search and Optimisation"],"videos":[],"references":[{"position":1,"raw":"[Boyarski et al., 2015] Boyarski, E.; Felner, A.; Stern, R.; Sharon, G.; Tolpin, D.; Betzalel, O.; and Shimony, S. 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