A generative bottom-up approach to the understanding of the development of rural societies

Abstract

This study analyses the complexity in determining the physical carrying capacity of a society in a specific environmental setting, and highlights the necessity for developing an agent-based modelling approach. In the context of this generative bottom-up approach, this study introduces an artificial agricultural society model developed in terms of the complex interactions among intelligent agents over space and time. Sample simulation results are presented to show the emergent macroscopic patterns of agricultural land use and of agents travel and transport networks around a market, along the variations of society s demography and agents trading prices at various time scales. The implications of the simulated results for policy making are also analysed.