On the universal combination function and the universal difference equation for reified temporal-causal network models

Research output: Chapter in Book / Report / Conference proceedingChapterAcademicpeer-review

Abstract

The universal differential and difference equation form an important basis for reified temporal-causal networks and their implementation. In this chapter, a more in depth analysis is presented of the universal differential and difference equation. It is shown how these equations can be derived in a direct manner and they are illustrated by some examples. Due to the existence of these universal difference and differential equation, the class of temporal-causal networks is closed under reification: by them it can be guaranteed that any reification of a temporal-causal network is itself also a temporal-causal network. That means that dedicated modeling and analysis methods for temporal-causal networks can also be applied to reified temporal-causal networks. In particular, it guarantees that reification can be done iteratively in order to obtain multilevel reified network models that are very useful to model multiple orders of adaptation. Moreover, as shown in Chap. 9, the universal difference equation enables that software of a very compact form can be developed, as all reification levels are handled by one computational reified network engine in the same manner. Alternatively, it is shown how the universal difference or differential equation can be used for compilation by multiple substitution for all states, which leads to another form of implementation. The background of these issues is discussed in the current chapter.

Original languageEnglish
Title of host publicationNetwork-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models
EditorsJan Treur
PublisherSpringer International Publishing AG
Chapter10
Pages225-247
Number of pages23
DOIs
Publication statusPublished - 1 Jan 2020

Publication series

NameStudies in Systems, Decision and Control
Volume251
ISSN (Print)2198-4182
ISSN (Electronic)2198-4190

Fingerprint

Causal Model
Difference equations
Difference equation
Network Model
Differential equations
reification
Differential equation
Multilevel Models
Substitution reactions
Multiple Models
Compilation
Network model
Engines
Substitution
substitution
Engine
guarantee
Closed
Software
Reification

Cite this

Treur, J. (2020). On the universal combination function and the universal difference equation for reified temporal-causal network models. In J. Treur (Ed.), Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models (pp. 225-247). (Studies in Systems, Decision and Control; Vol. 251). Springer International Publishing AG. https://doi.org/10.1007/978-3-030-31445-3_10
Treur, Jan. / On the universal combination function and the universal difference equation for reified temporal-causal network models. Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models. editor / Jan Treur. Springer International Publishing AG, 2020. pp. 225-247 (Studies in Systems, Decision and Control).
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Treur, J 2020, On the universal combination function and the universal difference equation for reified temporal-causal network models. in J Treur (ed.), Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models. Studies in Systems, Decision and Control, vol. 251, Springer International Publishing AG, pp. 225-247. https://doi.org/10.1007/978-3-030-31445-3_10

On the universal combination function and the universal difference equation for reified temporal-causal network models. / Treur, Jan.

Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models. ed. / Jan Treur. Springer International Publishing AG, 2020. p. 225-247 (Studies in Systems, Decision and Control; Vol. 251).

Research output: Chapter in Book / Report / Conference proceedingChapterAcademicpeer-review

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Treur J. On the universal combination function and the universal difference equation for reified temporal-causal network models. In Treur J, editor, Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models. Springer International Publishing AG. 2020. p. 225-247. (Studies in Systems, Decision and Control). https://doi.org/10.1007/978-3-030-31445-3_10