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A Functional Contextual Account of Background Knowledge in Categorization: Implications for Artificial General Intelligence and Cognitive Accounts of General Knowledge

Darren Edwards Orcid Logo, Ciara McEnteggart, Yvonne Barnes-Holmes

Frontiers in Psychology, Volume: 13

Swansea University Author: Darren Edwards Orcid Logo

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DOI (Published version): 10.3389/fpsyg.2022.745306

Abstract

Psychology has benefited from an enormous wealth of knowledge about processes of cognition in relation to how the brain organizes information. Within the categorization literature, this behavior is often explained through theories of memory construction called exemplar theory and prototype theory wh...

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Published in: Frontiers in Psychology
ISSN: 1664-1078
Published: Frontiers Media SA 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa59384
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spelling 2022-03-02T10:37:11.9861243 v2 59384 2022-02-13 A Functional Contextual Account of Background Knowledge in Categorization: Implications for Artificial General Intelligence and Cognitive Accounts of General Knowledge bee507022c083d875238b7802b96cbeb 0000-0002-2143-1198 Darren Edwards Darren Edwards true false 2022-02-13 PHAC Psychology has benefited from an enormous wealth of knowledge about processes of cognition in relation to how the brain organizes information. Within the categorization literature, this behavior is often explained through theories of memory construction called exemplar theory and prototype theory which are typically based on similarity or rule functions as explanations of how categories emerge. Although these theories work well at modeling highly controlled stimuli in laboratory settings, they often perform less well outside of these settings, such as explaining the emergence of background knowledge processes. In order to explain background knowledge, we present a non-similarity-based post-Skinnerian theory of human language called Relational Frame Theory (RFT) which is rooted in a philosophical world view called functional contextualism (FC). This theory offers a very different interpretation of how categories emerge through the functions of behavior and through contextual cues, which may be of some benefit to existing categorization theories. Specifically, RFT may be able to offer a novel explanation of how background knowledge arises, and we provide some mathematical considerations in order to identify a formal model. Finally, we discuss much of this work within the broader context of general semantic knowledge and artificial intelligence research. Journal Article Frontiers in Psychology 13 Frontiers Media SA 1664-1078 functional contextualism, machine learning, Relational Frame Theory (RFT), categorization,background knowledge 2 3 2022 2022-03-02 10.3389/fpsyg.2022.745306 COLLEGE NANME Public Health COLLEGE CODE PHAC Swansea University Other 2022-03-02T10:37:11.9861243 2022-02-13T12:13:34.5455988 Faculty of Medicine, Health and Life Sciences School of Health and Social Care - Public Health Darren Edwards 0000-0002-2143-1198 1 Ciara McEnteggart 2 Yvonne Barnes-Holmes 3 59384__22492__8a75be4a7a6c4df6bdf8475b464804ee.pdf 59384.pdf 2022-03-02T10:34:36.3178056 Output 11690843 application/pdf Version of Record true © 2022 Edwards, McEnteggart and Barnes-Holmes. This is an openaccess article distributed under the terms of the Creative Commons Attribution License (CC BY) true eng http://creativecommons.org/licenses/by/4.0/
title A Functional Contextual Account of Background Knowledge in Categorization: Implications for Artificial General Intelligence and Cognitive Accounts of General Knowledge
spellingShingle A Functional Contextual Account of Background Knowledge in Categorization: Implications for Artificial General Intelligence and Cognitive Accounts of General Knowledge
Darren Edwards
title_short A Functional Contextual Account of Background Knowledge in Categorization: Implications for Artificial General Intelligence and Cognitive Accounts of General Knowledge
title_full A Functional Contextual Account of Background Knowledge in Categorization: Implications for Artificial General Intelligence and Cognitive Accounts of General Knowledge
title_fullStr A Functional Contextual Account of Background Knowledge in Categorization: Implications for Artificial General Intelligence and Cognitive Accounts of General Knowledge
title_full_unstemmed A Functional Contextual Account of Background Knowledge in Categorization: Implications for Artificial General Intelligence and Cognitive Accounts of General Knowledge
title_sort A Functional Contextual Account of Background Knowledge in Categorization: Implications for Artificial General Intelligence and Cognitive Accounts of General Knowledge
author_id_str_mv bee507022c083d875238b7802b96cbeb
author_id_fullname_str_mv bee507022c083d875238b7802b96cbeb_***_Darren Edwards
author Darren Edwards
author2 Darren Edwards
Ciara McEnteggart
Yvonne Barnes-Holmes
format Journal article
container_title Frontiers in Psychology
container_volume 13
publishDate 2022
institution Swansea University
issn 1664-1078
doi_str_mv 10.3389/fpsyg.2022.745306
publisher Frontiers Media SA
college_str Faculty of Medicine, Health and Life Sciences
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hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str School of Health and Social Care - Public Health{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}School of Health and Social Care - Public Health
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description Psychology has benefited from an enormous wealth of knowledge about processes of cognition in relation to how the brain organizes information. Within the categorization literature, this behavior is often explained through theories of memory construction called exemplar theory and prototype theory which are typically based on similarity or rule functions as explanations of how categories emerge. Although these theories work well at modeling highly controlled stimuli in laboratory settings, they often perform less well outside of these settings, such as explaining the emergence of background knowledge processes. In order to explain background knowledge, we present a non-similarity-based post-Skinnerian theory of human language called Relational Frame Theory (RFT) which is rooted in a philosophical world view called functional contextualism (FC). This theory offers a very different interpretation of how categories emerge through the functions of behavior and through contextual cues, which may be of some benefit to existing categorization theories. Specifically, RFT may be able to offer a novel explanation of how background knowledge arises, and we provide some mathematical considerations in order to identify a formal model. Finally, we discuss much of this work within the broader context of general semantic knowledge and artificial intelligence research.
published_date 2022-03-02T04:16:39Z
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