A Cognitive Architecture for Mental Processes Involving Mental Models Analysed from a Self-modeling Network Viewpoint

Laila van Ments, Raj Bhalwankar, Jan Treur*

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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Abstract

This paper contributes an analysis of how in mental and social processes, humans often apply specific mental models and learn and adapt them in a controlled manner. It is discussed how controlled adaptation relates to the Plasticity Versus Stability Conundrum in neuroscience. From the analysis an informal three-level cognitive architecture for controlled adaptation was obtained. It is discussed here from a self-modeling network viewpoint how this cognitive architecture can be modeled as a self-modeling network. Making use of the specific network characteristics offered by the self-modeling network structure format, a large number of options for different types of adaptation of mental models and different types of control over adaptation of mental models were obtained. Many of these options were illustrated by a several realistic examples that were formalized by self-modeling networks. Other options that were distinguished from the analysis here, are offered as interesting options for future research.

Original languageEnglish
Title of host publicationData Science and Intelligent Systems
Subtitle of host publicationProceedings of 5th Computational Methods in Systems and Software 2021, Vol. 2
EditorsRadek Silhavy, Petr Silhavy, Zdenka Prokopova
PublisherSpringer Science and Business Media Deutschland GmbH
Pages628-647
Number of pages20
Volume2
ISBN (Electronic)9783030903213
ISBN (Print)9783030903206
DOIs
Publication statusPublished - 2021
Event5th Computational Methods in Systems and Software, CoMeSySo 2021 - Virtual, Online
Duration: 1 Oct 20211 Oct 2021

Publication series

NameLecture Notes in Networks and Systems
PublisherSpringer
Volume231 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference5th Computational Methods in Systems and Software, CoMeSySo 2021
CityVirtual, Online
Period1/10/211/10/21

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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