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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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