Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 240-249 |
| Number of pages | 10 |
| Journal | Journal of Theoretical and Applied Information Technology |
| Volume | 86 |
| Issue number | 2 |
| Publication status | Published - 20 Apr 2016 |
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
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Towards a self-adaptive agent-based simulation model. / Loo, Yim Ling; Tang, Yee Chong; Ahmad, Azhana; Mustapha, Aida.
In: Journal of Theoretical and Applied Information Technology, Vol. 86, No. 2, 20.04.2016, p. 240-249.Research output: Contribution to journal › Article
TY - JOUR
T1 - Towards a self-adaptive agent-based simulation model
AU - Loo, Yim Ling
AU - Tang, Yee Chong
AU - Ahmad, Azhana
AU - Mustapha, Aida
PY - 2016/4/20
Y1 - 2016/4/20
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=84964239610&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:84964239610
VL - 86
SP - 240
EP - 249
JO - Journal of Theoretical and Applied Information Technology
JF - Journal of Theoretical and Applied Information Technology
SN - 1992-8645
IS - 2
ER -