期刊名称：Journal of Artificial Societies and Social Simulation
印刷版ISSN：1460-7425
出版年度：2018
卷号：21
期号：4
页码：1-17
DOI：10.18564/jasss.3790
出版社：University of Surrey, Department of Sociology
摘要：Agent based modelling is nowadays widely used in transport and the social science. Forecasting population evolution and analysing the impact of hypothetical policies are o en the main goal of these developments. Such models are based on sub-models defining the interactions of agents either with other agents or with their environment. Sometimes, several models represent phenomena arising at the same time in the real life. Hence, the question of the order in which these sub-models need to be applied is very relevant for simulation outcomes. This paper aims to analyse and quantify the impact of the change in the order of sub-models on an evolving population modelled using TransMob. This so ware simulates the evolution of the population of a metropolitan area in South East of Sydney (Australia). It includes five principal models: ageing, death, birth, marriage and divorce. Each possible order implies slightly dierent results mainly driven by how agents’ ageing is defined with respect to death. Furthermore, we present a calendar-based approach for the ordering that decreases the variability of final populations. Finally, guidelines are provided proposing general advices and recommendations for researchers designing discrete time agent-based models.
关键词：Microsimulation; Agent-Based Modelling; Ordering of Models; Population Evolution; Robustness
