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dc.contributor.authorCazenave, Tristan
dc.date.accessioned2010-11-19T08:23:29Z
dc.date.available2010-11-19T08:23:29Z
dc.date.issued2010
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/5116
dc.language.isoenen
dc.subjectA*en
dc.subjectPartial Move A*en
dc.subjectshortest path problemen
dc.subject.ddc006.3en
dc.titlePartial Move A*en
dc.typeCommunication / Conférence
dc.description.abstractenSome shortest path problems that can be solved using the A* algorithm have a large branching factor due to the combination of multiple choices at each move. Multiple sequence alignment and multi-agent pathfinding are examples of such problems. If the search can be stopped after each choice instead of being stopped at each combination of choices, it takes much less memory and much less time. The goal of the paper is to show that Partial Move A* is much better than A* for these problems when the branching factor is large due to a large combination of choices at each move. When there is such a large combination of choices at each move, Partial Move A* can yield large memory gains and speedups over regular A*.en
dc.identifier.citationpages25-31en
dc.relation.ispartoftitle22nd IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2010 - proceedings
dc.relation.ispartofpublnameIEEE
dc.relation.ispartofdate2010
dc.relation.isversionofdoihttp://dx.doi.org/10.1109/ICTAI.2010.79
dc.description.sponsorshipprivateouien
dc.subject.ddclabelIntelligence artificielleen
dc.relation.ispartofisbn978-1-4244-8817-9
dc.relation.conftitle22th International Conference on Tools with Artificial Intelligenceen
dc.relation.confdate2010-10
dc.relation.confcityArrasen
dc.relation.confcountryFranceen


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