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

Laila van Ments, Rajesh Bhalwankar, Jan Treur

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

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. 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 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 publicationProc. of the 5th International Conference on Computational Methods in Systems and Software, CoMeSySo'21
PublisherSpringer Nature Switzerland AG
Publication statusAccepted/In press - 20 Jul 2021

Publication series

NameLecture Notes in Networks and Systems
PublisherSpringer Nature

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