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Exploiting landmarks for hybrid planning

dc.contributor.authorElkawkagy, Mohameden
dc.contributor.authorBercher, Pascalen
dc.contributor.authorSchattenberg, Bernden
dc.contributor.authorBiundo, Susanneen
dc.date.accessioned2025-06-11T07:35:55Z
dc.date.available2025-06-11T07:35:55Z
dc.date.issued2010en
dc.description.abstractVery recently, the well-known concept of landmarks has been adapted from the classical planning setting to hierarchical planning. It was shown how a pre-processing step that extracts local landmarks from a planning domain and problem description can be used in order to prune the search space that is to be explored before the actual search is performed. This pruning technique eliminates all branches of the task decomposition tree, for which can be proven that they will never lead to a solution. In this paper, we investigate this technique in more detail and extend it by introducing search strategies which use these local landmarks in order to guide the planning process more effectively towards a solution. Our empirical evaluation shows that the pre-processing step dramatically improves performance because dead ends can be detected much earlier than without pruning and that our search strategies using the local landmarks outperform many other possible search strategies.en
dc.description.statusPeer-revieweden
dc.format.extent12en
dc.identifier.otherORCID:/0000-0002-0795-4320/work/162949650en
dc.identifier.scopus84896627718en
dc.identifier.urihttp://www.scopus.com/inward/record.url?scp=84896627718&partnerID=8YFLogxKen
dc.identifier.urihttps://hdl.handle.net/1885/733758364
dc.language.isoenen
dc.relation.ispartofseries25th KI Workshop on Planen, Scheduling und Konfigurieren, Entwerfen 201025th KI Workshop on Planning, Scheduling, Configuration, and Design 2010en
dc.titleExploiting landmarks for hybrid planningen
dc.typeConference paperen
dspace.entity.typePublicationen
local.bibliographicCitation.lastpage12en
local.bibliographicCitation.startpage1en
local.contributor.affiliationElkawkagy, Mohamed; Ulm Universityen
local.contributor.affiliationBercher, Pascal; Institute of Artificial Intelligenceen
local.contributor.affiliationSchattenberg, Bernd; Ulm Universityen
local.contributor.affiliationBiundo, Susanne; Ulm Universityen
local.identifier.purefb942bc2-a1c3-4eef-87fa-93add0851b05en
local.identifier.urlhttps://www.scopus.com/pages/publications/84896627718en
local.type.statusPublisheden

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