Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/1368
Full metadata record
DC FieldValueLanguage
dc.contributor.authorJANSSENS, Davy-
dc.contributor.authorLan, Y-
dc.contributor.authorWETS, Geert-
dc.contributor.authorChen, G-
dc.date.accessioned2007-04-13T10:30:32Z-
dc.date.available2007-04-13T10:30:32Z-
dc.date.issued2006-
dc.identifier.citationISKE 2006, International Conference on Intelligent Systems and Knowledge Engineering, Shangai, China.-
dc.identifier.urihttp://hdl.handle.net/1942/1368-
dc.description.abstractGiven a sequence of activities and transport modes, this paper evaluates the use of a Reinforcement Machine Learning technique. The technique simulates time and location allocation for a given set of sequences and enables the prediction of a more complete and consistent activity pattern. A computer code has been established to automate the process and has been validated on empirical data.-
dc.format.extent52000 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.titleThe optimization of activity-travel sequences by means of reinforcement learning-
dc.typeConference Material-
local.bibliographicCitation.conferencenameISKE 2006, International Conference on Intelligent Systems and Knowledge Engineering-
local.bibliographicCitation.conferenceplaceShangai, China-
local.bibliographicCitation.jcatC2-
local.type.specifiedConference Material-
dc.bibliographicCitation.oldjcat-
item.contributorJANSSENS, Davy-
item.contributorLan, Y-
item.contributorWETS, Geert-
item.contributorChen, G-
item.fullcitationJANSSENS, Davy; Lan, Y; WETS, Geert & Chen, G (2006) The optimization of activity-travel sequences by means of reinforcement learning. In: ISKE 2006, International Conference on Intelligent Systems and Knowledge Engineering, Shangai, China..-
item.fulltextWith Fulltext-
item.accessRightsOpen Access-
Appears in Collections:Research publications
Files in This Item:
File Description SizeFormat 
optimization.pdfConference material50.78 kBAdobe PDFView/Open
Show simple item record

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.