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MAS/LUCC Resource Page: Introduction

Purpose and Definition
An increasing number of scholars are exploring the potential of agent-based or multi-agent system tools for modeling human land-use decisions and subsequent land-cover change. In an agent-based model, individual agents (representing, for example, migrant populations, landowner households, or local governments) autonomously make decisions based on internal rules and local information. While agent interactions may lead to recognizably structured outcomes, a set of equilibrium conditions is not imposed on these models, in contrast to modeling techniques such as mathematical programming or econometrics. Thus, these models potentially offer a high degree of flexibility for accounting for heterogeneity and interdependencies among agents and their environment. Further, when coupled with a cellular model representing the landscape on which agents act, these models are well suited for explicit representation of spatial processes, spatial interactions, and multi-scale phenomena.  Such coupled models are referred to as MAS/LUCC models (multi-agent system models of land-use and land-cover change) (Parker et. al, 2003)

This site provides a collection of resources for scholars interested in MAS/LUCC models.  The site has been developed as a follow-up to a special workshop on agent-based models of land use in 2001, co-sponsored by CSISS and LUCC Focus 1.  Since MAS/LUCC modeling is a relatively new area of research, the quantity of informal work surpasses the quantity of peer-reviewed published literature.  Further, the interdisciplinary nature of the field potentially inhibits communication between researchers from the diverse disciplines involved, which include geography, landscape ecology, regional science, agricultural and resource economics, anthropology, political science, and computer science .  We provide links to relevant literature, conferences and workshops, descriptions of ongoing research projects, and software tools both as an introduction to those new to this modeling field and as a shared resource for the community of modelers already involved in MAS/LUCC research.

Dawn Parker
George Mason University

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MAS/LUCC Resource Manager: Dawn Parker