Agent-based Modelling in the Agricultural Economics Tradition of Recursive Farm Modelling and Adaptive Micro-Systems

Publication Type

Conference proceedings

Authors

Berger, T., Troost, C.

Year of publication

2012

Published in

International Environmental Modelling and Software Society (iEMSs)

Conference name

2012 International Congress on Environmental Modelling and Software Managing Resources of a Limited Planet, Sixth Biennial Meeting

Conference location

Leipzig, Germany

Conference date

1.7. - 5.7.2012

Keywords

sustainability

Among model developers, a consensus has grown that environmental simulation models should ideally give a balanced representation of the economic, environmental, as well as social dimensions of a given system. Agent-based models or multi-agent systems (MAS) have been suggested as one possible balanced approach to capture especially the externalities and feedbacks between resource users in Social-Ecological Systems. Following the definition of Parker et al. (2002), multi-agent models of land-use/-cover change (MAS/LUCC) couple a cellular component that represents a landscape with an agent-based component that represents human decision-making. Various layers of landscape and agent properties and processes are combined into a spatial, cell-based framework, for example plots that produce biomass and farm-holdings that make land-use decisions. The behaviour of each landscape unit and each agent is represented by specific modules such as crop growth modules and agent decision modules. Parker et al. (2002) distinguish the following classes of MAS/LUCC: (1) abstract, (2) experimental, (3) historical, and (4) empirical applications. For example, Companion Modelling, which combines MAS with group discussions and role-playing games, falls into class (2), whereas agent-based modelling in the agricultural economics tradition falls into class (4). The paper discusses the particular purpose of the agricultural economics modelling approach, the real-world system entities and interactions captured, its data requirements, methods for uncertainty and sensitivity testing, and its applicability for interactive modelling and policy assessment.