文章基本信息

标题：TOWARDS A SELF-ADAPTIVE AGENT-BASED SIMULATION MODEL
本地全文：下载
作者：YIM LING LOO ; ALICIA Y.C. TANG ; AZHANA AHMAD 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2016
卷号：86
期号：2
出版社：Journal of Theoretical and Applied
摘要：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.
关键词：Self-adaptive Model; Agent-based Simulation Model; Processes Simulation; Extensive Model; Model Reuse and Replication