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A hybrid agent-based model integrated with a multi-stage learning-based fuzzy cognitive map

A hybrid agent-based model integrated with a multi-stage learning-based fuzzy cognitive map This article proposes a novel hybrid simulation model for understanding the complex tobacco use behavior.Design/methodology/approachThe model is developed by embedding the concept of the multistage learning-based fuzzy cognitive map (FCM) into the agent-based model (ABM) in order to benefit from advantageous of each methodology. The ABM is used to represent individual level behaviors while the FCM is used as a decision support mechanism for individuals. In this study, socio-demographic characteristics of individuals, tobacco control policies, and social network effect are taken into account to reflect the current tobacco use system of Turkey. The effects of plain package and COVID-19 on tobacco use behaviors of individuals are also searched under different scenarios.FindingsThe findings indicate that the proposed model provides promising results for representing the mental models of agents. Besides, the scenario analyses help to observe the possible reactions of people to new conditions according to characteristics.Originality/valueThe proposed method combined ABM and FCM with a multi-stage learning phases for modeling a complex and dynamic social problem as close as real life. It is expected to contribute for both ABM and tobacco use literature. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Kybernetes Emerald Publishing

A hybrid agent-based model integrated with a multi-stage learning-based fuzzy cognitive map

Kocabey Ciftci, Pinar; Unutmaz Durmusoglu, Zeynep Didem
Kybernetes , Volume 53 (10): 22 – Oct 30, 2024
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References (32)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0368-492X
DOI
10.1108/k-01-2023-0104
Publisher site
See Article on Publisher Site

Abstract

This article proposes a novel hybrid simulation model for understanding the complex tobacco use behavior.Design/methodology/approachThe model is developed by embedding the concept of the multistage learning-based fuzzy cognitive map (FCM) into the agent-based model (ABM) in order to benefit from advantageous of each methodology. The ABM is used to represent individual level behaviors while the FCM is used as a decision support mechanism for individuals. In this study, socio-demographic characteristics of individuals, tobacco control policies, and social network effect are taken into account to reflect the current tobacco use system of Turkey. The effects of plain package and COVID-19 on tobacco use behaviors of individuals are also searched under different scenarios.FindingsThe findings indicate that the proposed model provides promising results for representing the mental models of agents. Besides, the scenario analyses help to observe the possible reactions of people to new conditions according to characteristics.Originality/valueThe proposed method combined ABM and FCM with a multi-stage learning phases for modeling a complex and dynamic social problem as close as real life. It is expected to contribute for both ABM and tobacco use literature.

Journal

Kybernetes – Emerald Publishing

Published: Oct 30, 2024

Keywords: Agent-based modeling; Fuzzy cognitive map; Nonlinear Hebbian learning; Extended great deluge algorithm; Tobacco use

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