Towards a self-adaptive agent-based simulation model

Agent-based simulation (ABS) modelling has been a widely applied approach for simulating domain-specific phenomena. Currently, parameters and environments are simulated by a domain-specific model that is strictly used proprietarily by the ABS model developer. This causes inflexibility towards extens...

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Main Authors: Loo, Y.L., Tang, A.Y.C., Ahmad, A., Mustapha, A.
Format: Article
Language:English
Published: 2017
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spelling my.uniten.dspace-39602018-01-26T01:50:39Z Towards a self-adaptive agent-based simulation model Loo, Y.L. Tang, A.Y.C. Ahmad, A. Mustapha, A. Agent-based simulation (ABS) modelling has been a widely applied approach for simulating domain-specific phenomena. Currently, parameters and environments are simulated by a domain-specific model that is strictly used proprietarily by the ABS model developer. This causes inflexibility towards extension of the developed ABS model, which will further result in difficulties for validation and verification of the robustness and reliability of the ABS model. To address this issue, this paper proposes a self-adaptive ABS model that is capable of modelling cross-domain phenomena by selecting the required parameters based on the environment. The capability to self-adapt will allow the model to be easily extended and replicated. The self-adapt capability is enabled by a governing algorithm within the model and is conceptually illustrated through a case study of crime report process ABS modelling. © 2005 - 2016 JATIT & LLS. All rights reserved. 2017-11-01T05:56:35Z 2017-11-01T05:56:35Z 2016 Article https://pure.uniten.edu.my/en/persons/azhana-ahmad/publications/ en Journal of Theoretical and Applied Information Technology Volume 86, Issue 2, 20 April 2016, Pages 240-249
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
description Agent-based simulation (ABS) modelling has been a widely applied approach for simulating domain-specific phenomena. Currently, parameters and environments are simulated by a domain-specific model that is strictly used proprietarily by the ABS model developer. This causes inflexibility towards extension of the developed ABS model, which will further result in difficulties for validation and verification of the robustness and reliability of the ABS model. To address this issue, this paper proposes a self-adaptive ABS model that is capable of modelling cross-domain phenomena by selecting the required parameters based on the environment. The capability to self-adapt will allow the model to be easily extended and replicated. The self-adapt capability is enabled by a governing algorithm within the model and is conceptually illustrated through a case study of crime report process ABS modelling. © 2005 - 2016 JATIT & LLS. All rights reserved.
format Article
author Loo, Y.L.
Tang, A.Y.C.
Ahmad, A.
Mustapha, A.
spellingShingle Loo, Y.L.
Tang, A.Y.C.
Ahmad, A.
Mustapha, A.
Towards a self-adaptive agent-based simulation model
author_facet Loo, Y.L.
Tang, A.Y.C.
Ahmad, A.
Mustapha, A.
author_sort Loo, Y.L.
title Towards a self-adaptive agent-based simulation model
title_short Towards a self-adaptive agent-based simulation model
title_full Towards a self-adaptive agent-based simulation model
title_fullStr Towards a self-adaptive agent-based simulation model
title_full_unstemmed Towards a self-adaptive agent-based simulation model
title_sort towards a self-adaptive agent-based simulation model
publishDate 2017
_version_ 1644493583003156480
score 13.214268