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dc.contributor.authorLane, Peter
dc.contributor.authorGobet, F.
dc.contributor.authorPirrone, Angelo
dc.contributor.authorBartlett, Laura
dc.contributor.authorJaved, Noman
dc.date.accessioned2024-09-09T14:30:02Z
dc.date.available2024-09-09T14:30:02Z
dc.date.issued2023-06-13
dc.identifier.citationLane , P , Gobet , F , Pirrone , A , Bartlett , L & Javed , N 2023 , ' Synthesising cognitive models with genetic programming ' , Paper presented at School of Physics, Engineering and Computer Science Research Conference , Hatfield , United Kingdom , 13/06/23 - 13/06/23 pp. 1-3 .
dc.identifier.citationconference
dc.identifier.urihttp://hdl.handle.net/2299/28142
dc.description.abstractDeveloping, understanding and verifying the behaviour of cognitive models is a non-trivial task. A good cognitive model explains and predicts human behaviour in a particular experimental setting. Cognitive models are often in the form of computer programs which need to be designed and written for the given experiment and behaviour: time constraints or natural bias (oversights) often lead to models written by human programmers being constrained to particular theoretical assumptions. We apply program synthesis to this task, introducing novel training and post-processing techniques; our experiments automatically create good quality models, and help visualise the structure of the solution space.en
dc.format.extent3
dc.format.extent268341
dc.language.isoeng
dc.relation.ispartof
dc.titleSynthesising cognitive models with genetic programmingen
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionDepartment of Computer Science
dc.description.statusPeer reviewed
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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