Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/1168
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dc.contributor.authorFrias-Martinez, E-
dc.contributor.authorGobet, F-
dc.coverage.spatial24en
dc.date.accessioned2007-08-17T08:13:33Z-
dc.date.available2007-08-17T08:13:33Z-
dc.date.issued2007-
dc.identifier.citationFrias-Martinez , E., & Gobet, F. (in press). Automatic generation of cognitive theories using genetic programming. Minds & Machines.en
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/1168-
dc.description.abstractCognitive neuroscience is the branch of neuroscience that studies the neural mechanisms underpinning cognition and develops theories explaining them. Within cognitive neuroscience, computational neuroscience focuses on modeling behavior, using theories expressed as computer programs. Up to now, computational theories have been formulated by neuroscientists. In this paper, we present a new approach to theory development in neuroscience: the automatic generation and testing of cognitive theories using genetic programming. Our approach evolves from experimental data cognitive theories that explain “the mental program” that subjects use to solve a specific task. As an example, we have focused on a typical neuroscience experiment, the delayed-match-to-sample (DMTS) task. The main goal of our approach is to develop a tool that neuroscientists can use to develop better cognitive theories.en
dc.format.extent232320 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.publisherSpringer Verlagen
dc.subjectCognitive Neuroscienceen
dc.subjectComputational Neuroscienceen
dc.subjectTheory generationen
dc.subjectTheory buildingen
dc.subjectGenetic Programmingen
dc.subjectevolutionary computationen
dc.subjectDelayed-Match-To-Sampleen
dc.subjectscientific discoveryen
dc.subjectsearchen
dc.subjectfitness functionen
dc.subjecttree representationen
dc.subjectmodularityen
dc.subjecthierarchyen
dc.subjectbloatingen
dc.subjectcognitive architectureen
dc.subjectmemoryen
dc.titleAutomatic Generation of Cognitive Theories using Genetic Programmingen
dc.typeResearch Paperen
dc.identifier.doihttps://doi.org/10.1007/s11023-007-9070-6-
Appears in Collections:Psychology
Dept of Life Sciences Research Papers

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