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dc.contributor.author Shen, Qiang
dc.contributor.author Keppens, Jeroen
dc.date.accessioned 2008-01-23T11:24:09Z
dc.date.available 2008-01-23T11:24:09Z
dc.date.issued 2004
dc.identifier.citation Shen , Q & Keppens , J 2004 , ' Compositional model repositories via dynamic constraint satisfaction with order-of-magnitude preferences ' Journal of Artificial Intelligence Research , pp. 499-550 . en
dc.identifier.issn 1943-5037
dc.identifier.other PURE: 74637
dc.identifier.other dspace: 2160/462
dc.identifier.uri http://hdl.handle.net/2160/462
dc.identifier.uri http://www.jair.org/media/1335/live-1335-2271-jair.pdf en
dc.description J. Keppens and Q. Shen. Compositional model repositories via dynamic constraint satisfaction with order-of-magnitude preferences. Journal of Artificial Intelligence Research, 21:499-550, 2004. en
dc.description.abstract The predominant knowledge-based approach to automated model construction, compositional modelling, employs a set of models of particular functional components. Its inference mechanism takes a scenario describing the constituent interacting components of a system and translates it into a useful mathematical model. This paper presents a novel compositional modelling approach aimed at building model repositories. It furthers the field in two respects. Firstly, it expands the application domain of compositional modelling to systems that can not be easily described in terms of interacting functional components, such as ecological systems. Secondly, it enables the incorporation of user preferences into the model selection process. These features are achieved by casting the compositional modelling problem as an activity-based dynamic preference constraint satisfaction problem, where the dynamic constraints describe the restrictions imposed over the composition of partial models and the preferences correspond to those of the user of the automated modeller. In addition, the preference levels are represented through the use of symbolic values that differ in orders of magnitude. en
dc.format.extent 52 en
dc.language.iso eng
dc.relation.ispartof Journal of Artificial Intelligence Research en
dc.title Compositional model repositories via dynamic constraint satisfaction with order-of-magnitude preferences en
dc.type Text en
dc.type.publicationtype Article (Journal) en
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Advanced Reasoning Group en
dc.description.status Peer reviewed en


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