Towards a self-adaptive agent-based simulation model

Yim Ling Loo, Yee Chong Tang, Azhana Ahmad, Aida Mustapha

Research output: Contribution to journalArticle

1 Citation (Scopus)

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 languageEnglish
Pages (from-to)240-249
Number of pages10
JournalJournal of Theoretical and Applied Information Technology
Volume86
Issue number2
Publication statusPublished - 20 Apr 2016

Fingerprint

Agent-based Simulation
Agent-based Model
Simulation Model
Agent-based Modeling
Simulation Modeling
Verification and Validation
Process Simulation
Crime
Computer simulation
Strictly
Model
Robustness
Modeling

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

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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 journalArticle

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