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Improving Planning Performance Using Low-conflict Relaxed Plans

dc.contributor.authorBaier, Jorge
dc.contributor.authorBotea, Adi
dc.coverage.spatialThessaloniki Greece
dc.date.accessioned2015-12-07T22:41:20Z
dc.date.createdSeptember 19-23 2009
dc.date.issued2009
dc.date.updated2016-02-24T11:13:53Z
dc.description.abstractThe FF relaxed plan heuristic is one of the most effective techniques in domain-independent satisficing planning and is used by many state-of-the-art heuristic-search planners. However, it may sometimes provide quite inaccurate information, since its relaxation strategy, which ignores the delete effects of actions, may oversimplify a problem's structure. In this paper, we propose a novel algorithm for computing relaxed plans which - although still relaxed - aim at respecting much of the structure of the original problem. We accomplish this by generating relaxed plans with a reduced number of conflicts. An action a will add a conflict when added to a relaxed plan if the resulting plan is provably illegal (i.e, not executable) in the un-relaxed problem. As a second contribution, we propose a new lookahead strategy, in the spirit of Vidal's YAHSP lookahead, that can better exploit the contents of relaxed plans. In our experimental analysis, we show that the resulting heuristic improves over the FF heuristic in a number of domains, most notably when lookahead is enabled. Moreover, the resulting system, which uses our new lookahead, is competitive with state-of-the-art planners, and even better in terms of the number of solved problems.
dc.identifier.isbn9781577354062
dc.identifier.urihttp://hdl.handle.net/1885/24270
dc.publisherAAAI Press
dc.relation.ispartofseriesInternational conference on Automated planning and scheduling (ICAPS 2009)
dc.sourceProceedings of the Nineteenth International Conference on Automated Planning and Scheduling
dc.subjectKeywords: Experimental analysis; Inaccurate information; Look-ahead; Novel algorithm; Relaxation strategies; Relaxed problem; Satisficing; Algorithms; Planning
dc.titleImproving Planning Performance Using Low-conflict Relaxed Plans
dc.typeConference paper
local.contributor.affiliationBaier, Jorge, University of Toronto
local.contributor.affiliationBotea, Adi , College of Engineering and Computer Science, ANU
local.contributor.authoruidBotea, Adi , u1814829
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080199 - Artificial Intelligence and Image Processing not elsewhere classified
local.identifier.absfor080105 - Expert Systems
local.identifier.ariespublicationu4607519xPUB31
local.identifier.scopusID2-s2.0-78650600647
local.type.statusPublished Version

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