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

S. Sahand Mohammadi Ziabari; Jan Treur

doi:10.1007/978-981-15-0637-6_8

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 proceeding › Conference contribution › Academic › peer-review

289 Downloads (Pure)

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 language	English
Title of host publication	Fourth International Congress on Information and Communication Technology
Subtitle of host publication	ICICT 2019, London, Volume 1
Editors	Xin-She Yang, Simon Sherratt, Nilanjan Dey, Amit Joshi
Publisher	Springer
Pages	91-111
Number of pages	21
Volume	1
ISBN (Electronic)	9789811506376
ISBN (Print)	9789811506369
DOIs	https://doi.org/10.1007/978-981-15-0637-6_8
Publication status	Published - 2020
Event	4th International Congress on Information and Communication Technology, ICICT 2019 - London, United Kingdom Duration: 27 Feb 2019 → 28 Feb 2019

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1041
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	4th International Congress on Information and Communication Technology, ICICT 2019
Country/Territory	United Kingdom
City	London
Period	27/02/19 → 28/02/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 16 Peace, Justice and Strong Institutions

Keywords

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

Access to Document

10.1007/978-981-15-0637-6_8

MohammadiZiabari-Treur2020_Chapter_AModelingEnvironmentForDynamicFinal published version, 975 KBLicence: Article 25fa Dutch Copyright Act

https://www.researchgate.net/publication/330440560_A_Modeling_Environment_for_Dynamic_and_Adaptive_Network_Models_Implemented_in_Matlab

Persistent URL (handle)

Persistent link

Cite this

Mohammadi Ziabari, S. S., & Treur, J. (2020). A modeling environment for dynamic and adaptive network models implemented in matlab. In X.-S. Yang, S. Sherratt, N. Dey, & A. Joshi (Eds.), Fourth International Congress on Information and Communication Technology: ICICT 2019, London, Volume 1 (Vol. 1, pp. 91-111). (Advances in Intelligent Systems and Computing; Vol. 1041). Springer. https://doi.org/10.1007/978-981-15-0637-6_8

Mohammadi Ziabari, S. Sahand ; Treur, Jan. / A modeling environment for dynamic and adaptive network models implemented in matlab. Fourth International Congress on Information and Communication Technology: ICICT 2019, London, Volume 1. editor / Xin-She Yang ; Simon Sherratt ; Nilanjan Dey ; Amit Joshi. Vol. 1 Springer, 2020. pp. 91-111 (Advances in Intelligent Systems and Computing).

@inproceedings{68293bd06839426b9b07b2bb427f4f72,

title = "A modeling environment for dynamic and adaptive network models implemented in matlab",

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.",

keywords = "Adaptive, Bonding by homophily, Hebbian learning, MATLAB, Network-oriented modeling, Software environment, Temporal-causal network",

author = "\{Mohammadi Ziabari\}, \{S. Sahand\} and Jan Treur",

year = "2020",

doi = "10.1007/978-981-15-0637-6\_8",

language = "English",

isbn = "9789811506369",

volume = "1",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer",

pages = "91--111",

editor = "Xin-She Yang and Simon Sherratt and Nilanjan Dey and Amit Joshi",

booktitle = "Fourth International Congress on Information and Communication Technology",

note = "4th International Congress on Information and Communication Technology, ICICT 2019 ; Conference date: 27-02-2019 Through 28-02-2019",

}

Mohammadi Ziabari, SS & Treur, J 2020, A modeling environment for dynamic and adaptive network models implemented in matlab. in X-S Yang, S Sherratt, N Dey & A Joshi (eds), Fourth International Congress on Information and Communication Technology: ICICT 2019, London, Volume 1. vol. 1, Advances in Intelligent Systems and Computing, vol. 1041, Springer, pp. 91-111, 4th International Congress on Information and Communication Technology, ICICT 2019, London, United Kingdom, 27/02/19. https://doi.org/10.1007/978-981-15-0637-6_8

A modeling environment for dynamic and adaptive network models implemented in matlab. / Mohammadi Ziabari, S. Sahand; Treur, Jan.
Fourth International Congress on Information and Communication Technology: ICICT 2019, London, Volume 1. ed. / Xin-She Yang; Simon Sherratt; Nilanjan Dey; Amit Joshi. Vol. 1 Springer, 2020. p. 91-111 (Advances in Intelligent Systems and Computing; Vol. 1041).

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

TY - GEN

T1 - A modeling environment for dynamic and adaptive network models implemented in matlab

AU - Mohammadi Ziabari, S. Sahand

AU - Treur, Jan

PY - 2020

Y1 - 2020

N2 - 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.

AB - 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.

KW - Adaptive

KW - Bonding by homophily

KW - Hebbian learning

KW - MATLAB

KW - Network-oriented modeling

KW - Software environment

KW - Temporal-causal network

UR - https://www.scopus.com/pages/publications/85077132193

UR - https://www.scopus.com/pages/publications/85077132193#tab=citedBy

U2 - 10.1007/978-981-15-0637-6_8

DO - 10.1007/978-981-15-0637-6_8

M3 - Conference contribution

AN - SCOPUS:85077132193

SN - 9789811506369

VL - 1

T3 - Advances in Intelligent Systems and Computing

SP - 91

EP - 111

BT - Fourth International Congress on Information and Communication Technology

A2 - Yang, Xin-She

A2 - Sherratt, Simon

A2 - Dey, Nilanjan

A2 - Joshi, Amit

PB - Springer

T2 - 4th International Congress on Information and Communication Technology, ICICT 2019

Y2 - 27 February 2019 through 28 February 2019

ER -

Mohammadi Ziabari SS, Treur J. A modeling environment for dynamic and adaptive network models implemented in matlab. In Yang XS, Sherratt S, Dey N, Joshi A, editors, Fourth International Congress on Information and Communication Technology: ICICT 2019, London, Volume 1. Vol. 1. Springer. 2020. p. 91-111. (Advances in Intelligent Systems and Computing). Epub 2019 Dec 1. doi: 10.1007/978-981-15-0637-6_8

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

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Persistent URL (handle)

Other files and links

Fingerprint

Cite this