How Far Do Self-Modeling Networks Reach: Relating Them to Adaptive Dynamical Systems

Jan Treur

doi:10.1007/978-3-030-85821-6_20

How Far Do Self-Modeling Networks Reach: Relating Them to Adaptive Dynamical Systems

Jan Treur^*

^*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceeding › Chapter › Academic › peer-review

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Abstract

In this chapter, it is addressed by mathematical analysis how network-oriented modeling relates to the dynamical systems perspective on mental processes. It has been mathematically proven that any dynamical system can be modeled as a temporal-causal network model and that any adaptive dynamical system (of any order) can be modeled by a self-modeling network (of the same order).

Original language	English
Title of host publication	Mental Models and their Dynamics, Adaptation and Control
Subtitle of host publication	A Self-Modeling Network Modeling Approach
Editors	Jan Treur, Laila Van Ments
Publisher	Springer Nature Switzerland AG
Chapter	20
Pages	565-581
Number of pages	17
ISBN (Electronic)	9783030858216
ISBN (Print)	9783030858209
DOIs	https://doi.org/10.1007/978-3-030-85821-6_20
Publication status	Published - 2022

Publication series

Name	Studies in Systems, Decision and Control
Volume	394
ISSN (Print)	2198-4182
ISSN (Electronic)	2198-4190

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Adaptive dynamical systems
Applicability
Self-modeling networks

Access to Document

10.1007/978-3-030-85821-6_20

Treur2022_Chapter20_HowFarDoSelf-ModelingNetworksReachFinal published version, 519 KBLicence: Article 25fa Dutch Copyright Act

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Treur, J. (2022). How Far Do Self-Modeling Networks Reach: Relating Them to Adaptive Dynamical Systems. In J. Treur, & L. Van Ments (Eds.), Mental Models and their Dynamics, Adaptation and Control: A Self-Modeling Network Modeling Approach (pp. 565-581). (Studies in Systems, Decision and Control; Vol. 394). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-85821-6_20

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abstract = "In this chapter, it is addressed by mathematical analysis how network-oriented modeling relates to the dynamical systems perspective on mental processes. It has been mathematically proven that any dynamical system can be modeled as a temporal-causal network model and that any adaptive dynamical system (of any order) can be modeled by a self-modeling network (of the same order).",

keywords = "Adaptive dynamical systems, Applicability, Self-modeling networks",

author = "Jan Treur",

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year = "2022",

doi = "10.1007/978-3-030-85821-6\_20",

language = "English",

isbn = "9783030858209",

series = "Studies in Systems, Decision and Control",

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Treur, J 2022, How Far Do Self-Modeling Networks Reach: Relating Them to Adaptive Dynamical Systems. in J Treur & L Van Ments (eds), Mental Models and their Dynamics, Adaptation and Control: A Self-Modeling Network Modeling Approach. Studies in Systems, Decision and Control, vol. 394, Springer Nature Switzerland AG, pp. 565-581. https://doi.org/10.1007/978-3-030-85821-6_20

How Far Do Self-Modeling Networks Reach: Relating Them to Adaptive Dynamical Systems. / Treur, Jan.
Mental Models and their Dynamics, Adaptation and Control: A Self-Modeling Network Modeling Approach. ed. / Jan Treur; Laila Van Ments. Springer Nature Switzerland AG, 2022. p. 565-581 (Studies in Systems, Decision and Control; Vol. 394).

Research output: Chapter in Book / Report / Conference proceeding › Chapter › Academic › peer-review

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KW - Applicability

KW - Self-modeling networks

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Treur J. How Far Do Self-Modeling Networks Reach: Relating Them to Adaptive Dynamical Systems. In Treur J, Van Ments L, editors, Mental Models and their Dynamics, Adaptation and Control: A Self-Modeling Network Modeling Approach. Springer Nature Switzerland AG. 2022. p. 565-581. (Studies in Systems, Decision and Control). Epub 2022 Jan 26. doi: 10.1007/978-3-030-85821-6_20

How Far Do Self-Modeling Networks Reach: Relating Them to Adaptive Dynamical Systems

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Keywords

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