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dc.contributor.authorLane, P.C.R.
dc.contributor.authorGobet, F.
dc.date.accessioned2008-06-10T10:03:36Z
dc.date.available2008-06-10T10:03:36Z
dc.date.issued2005
dc.identifier.citationLane , P C R & Gobet , F 2005 , Applying Multi-Criteria Optimisation to Develop Cognitive Models . in In: Proceedings of the 2005 UK Workshop on Computational Intelligence . Birkbeck , pp. 28-35 .
dc.identifier.otherdspace: 2299/2080
dc.identifier.urihttp://hdl.handle.net/2299/2080
dc.description.abstractA scientific theory is developed by modelling empirical data in a range of domains. The goal of developing a theory is to optimise the t of the theory to as many experimental settings as possible, whilst retaining some qualitative properties such as `parsimony' or `comprehensibility'. We formalise the task of developing theories of human cognition as a problem in multi-criteria optimisation. There are many challenges in this task, including the representation of competing theories, coordinating the t with multiple experiments, and bringing together competing results to provide suitable theories. Experiments demonstrate the development of a theory of categorisation, using multiple optimisation criteria in genetic algorithms to locate pareto-optimal sets.en
dc.format.extent393925
dc.language.isoeng
dc.publisherBirkbeck
dc.relation.ispartofIn: Proceedings of the 2005 UK Workshop on Computational Intelligence
dc.titleApplying Multi-Criteria Optimisation to Develop Cognitive Modelsen
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionDepartment of Computer Science
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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