Multiple Representations in Cognitive Architectures

David Peebles, Peter Cheng

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

Abstract

The widely demonstrated ability of humans to deal with multiple representations of information has a number of important implications for a proposed standard model of the mind (SMM). In this paper we outline four and argue that a SMM must incorporate (a) multiple representational formats and (b) meta-cognitive processes that operate on them. We then describe current approaches to extend cognitive architectures with visual-spatial representations, in part to illustrate the limitations of current architectures in relation to the implications we raise but also to identify the basis upon which a consensus about the nature of these additional representations can be agreed. We believe that addressing these implications and outlining a specification for multiple representations should be a key goal for those seeking to develop a standard model of the mind.
Original languageEnglish
Title of host publication2017 AAAI Fall Symposium Series
Subtitle of host publicationFS-17-05: A Standard Model of the Mind
Place of PublicationPalo Alto, California
PublisherAssociation for the Advancement of Artificial Intelligence
Pages425-430
Number of pages6
ISBN (Print)9781577357940
Publication statusPublished - Dec 2017
EventAssociation for the Advancement of Artificial Intelligence Fall Symposium Series - The West Arlington Gateway, Arlington, United States
Duration: 9 Nov 201711 Nov 2017
https://www.aaai.org/Symposia/Fall/fss17symposia.php (Link to Event Details)

Conference

ConferenceAssociation for the Advancement of Artificial Intelligence Fall Symposium Series
CountryUnited States
CityArlington
Period9/11/1711/11/17
Internet address

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  • Cite this

    Peebles, D., & Cheng, P. (2017). Multiple Representations in Cognitive Architectures. In 2017 AAAI Fall Symposium Series: FS-17-05: A Standard Model of the Mind (pp. 425-430). Palo Alto, California: Association for the Advancement of Artificial Intelligence.