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A Dynamic Field Theoretic Model of Iowa Gambling Task Performance
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.ORCID iD: 0000-0002-1525-0745
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
2010 (English)In: 2010 IEEE 9th International Conference on Development and Learning (ICDL): Ann Arbor, MI, August 18-21, 2010, IEEE conference proceedings, 2010, p. 297-304Conference paper, Published paper (Refereed)
Abstract [en]

Choice behaviour where outcome-contingencies vary or are prohabilistic has been the focus of many benchmark tasks of infant to adult development in the psychology literature. Dynamic field theoretic (DFT) investigations of cognitive and behavioural competencies have been used in order to identify parameters critical to infant development. In this paper we report the findings of a DFT model that is able to replicate normal functioning adult  performance on the Iowa gambling task (IGT).  The model offers a simple demonstration proof of the parsimonious reversal learning alternative to Damasio’s somatic marker  explanation of IGT performance. Our simple model demonstrates a potentially important role for reinforcement/reward learning to generating behaviour that allows for advantageous performance. We compare our DFT modelling approach to one used on the A-not-B infant paradigm and suggest that a critical aspect of development lies in the ability to flexibly trade off perseverative versus exploratory behaviour in order to capture statistical choice-outcome contingencies. Finally, we discuss the importance of an investigation of the IGT in an embodied setting where reward prediction learning may provide critical means by which adaptive behavioural reversals can be enacted.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2010. p. 297-304
National Category
Computer and Information Sciences
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-4809DOI: 10.1109/DEVLRN.2010.5578826Scopus ID: 2-s2.0-78149243222ISBN: 978-1-4244-6902-4 ISBN: 1-4244-6902-3 ISBN: 978-1-4244-6900-0 ISBN: 1-4244-6900-7 OAI: oai:DiVA.org:his-4809DiVA, id: diva2:410012
Conference
2010 IEEE 9th International Conference on Development and Learning, Ann Arbor, MI, August 18-21, 2010
Available from: 2011-04-12 Created: 2011-04-12 Last updated: 2024-05-21Bibliographically approved

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Lowe, RobertDuran, BorisZiemke, Tom

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