Genetic Programming for Developing Simple Cognitive Models

Laura Bartlett, Angelo Pirrone, Noman Javed, Peter Lane, Fernand Gobet

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Frequently in psychology, simple tasks that are designed to tap a particular feature of cognition are used without considering the other mechanisms that might be at play. For example, the delayed-match-to-sample (DMTS) task is often used to examine short-term memory; however, a number of cognitive mechanisms interact to produce the observed behaviour, such as decision-making and attention processes. As these simple tasks form the basis of more complex psychological experiments and theories, it is critical to understand what strategies might be producing the recorded behaviour. The current paper uses the GEMS methodology, a system that generates models of cognition using genetic programming, and applies it to differing DMTS experimental conditions. We investigate the strategies that participants might be using, while looking at similarities and differences in strategy depending on task variations; in this case, changes to the interval between study and recall affected the strategies used by the generated models.
Original languageEnglish
Title of host publicationProceedings of the 45th Annual Conference of the Cognitive Science Society
Place of PublicationSydney, Australia
PublisherCognitive Science Society
Pages2833-2839
Number of pages7
Publication statusPublished - 29 Jul 2023
Event45th Annual Meeting of the Cognitive Science Society - Sidney, Australia
Duration: 26 Jul 202329 Jul 2023
Conference number: 45
https://cognitivesciencesociety.org/cogsci-2023/

Publication series

NameProceedings of the Annual Meeting of the Cognitive Science Society
PublisherCognitive Science Society
Volume45
ISSN (Print)1069-7977

Conference

Conference45th Annual Meeting of the Cognitive Science Society
Abbreviated titleCOGSCI 2023
Country/TerritoryAustralia
CitySidney
Period26/07/2329/07/23
Internet address

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