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A Modeling Environment for Reified Temporal-Causal Network Models

  • Jan TreurEmail author
Chapter
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 251)

Abstract

The introduced multilevel reified (temporal-causal) network architecture is the basis of the implementation of a dedicated software environment developed by the author in Matlab. The environment includes a combination function library and a generic computational reified network engine. It uses role matrices specifying the characteristics for the designed network model as input. Based on this input, the computational reified network engine can be used to generate simulations for the network model, thereby using combination functions from the library. In this chapter, this software environment is described in more detail.

References

  1. Treur, J.: Network-Oriented Modeling: Addressing Complexity of Cognitive, Affective and Social Interactions. Springer Publishers (2016) Google Scholar
  2. Treur, J.: Network reification as a unified approach to represent network adaptation principles within a network. In: Proceedings of the 7th International Conference on Natural Computing. Lecture Notes in Computer Science, vol 11324, pp. 344–358. Springer Publishers (2018a)Google Scholar
  3. Treur, J.: Multilevel network reification: representing higher-order adaptivity in a network. In: Proceedings of the 7th International Conference on Complex Networks and their Applications, Complex Networks’ 18, vol. 1. Studies in Computational Intelligence, vol. 812, pp. 635–651. Springer (2018b)Google Scholar
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  5. Treur, J.: Design of a Software Architecture for Multilevel Reified Temporal-Causal Networks (2019b). Doi:  https://doi.org/10.13140/rg.2.2.23492.07045. Url: https://www.researchgate.net/publication/333662169

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Social AI Group, Department of Computer ScienceVrije Universiteit AmsterdamAmsterdamThe Netherlands

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