A modeling environment for dynamic and adaptive network models implemented in matlab

S. Sahand Mohammadi Ziabari*, Jan Treur

*Corresponding author for this work

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

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Abstract

In this paper, a software environment to support Network-Oriented Modeling is presented. The environment has been implemented in MATLAB. This code covers the principles of temporal-causal network models. The software environment has built-in options for network adaptation principles such as the Hebbian learning principle from neuroscience and the adaptation principle for bonding based on homophily from social science. The implementation is illustrated for an adaptive temporal-causal network model under acute stress for decision-making.

Original languageEnglish
Title of host publicationFourth International Congress on Information and Communication Technology
Subtitle of host publicationICICT 2019, London, Volume 1
EditorsXin-She Yang, Simon Sherratt, Nilanjan Dey, Amit Joshi
PublisherSpringer
Pages91-111
Number of pages21
Volume1
ISBN (Electronic)9789811506376
ISBN (Print)9789811506369
DOIs
Publication statusPublished - 2020
Event4th International Congress on Information and Communication Technology, ICICT 2019 - London, United Kingdom
Duration: 27 Feb 201928 Feb 2019

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1041
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference4th International Congress on Information and Communication Technology, ICICT 2019
CountryUnited Kingdom
CityLondon
Period27/02/1928/02/19

Keywords

  • Adaptive
  • Bonding by homophily
  • Hebbian learning
  • MATLAB
  • Network-oriented modeling
  • Software environment
  • Temporal-causal network

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