This article presents an overview of multi-agent system models of land-use/cover change (MAS/LUCC models). This special class of LUCC models combines a cellular landscape model with agent-based representations of decision making, integrating the two components through specification of interdependencies and feedbacks between agents and their environment. The authors review alternative LUCC modeling techniques and discuss the ways in which MAS/LUCC models may overcome some important limitations of existing techniques. We briefly review ongoing MAS/LUCC modeling efforts in four research areas. We discuss the potential strengths of MAS/LUCC models and suggest that these strengths guide researchers in assessing the appropriate choice of model for their particular research question. We find that MAS/LUCC models are particularly well suited for representing complex spatial interactions under heterogeneous conditions and for modeling decentralized, autonomous decision making. We discuss a range of possible roles for MAS/LUCC models, from abstract models designed to derive stylized hypotheses to empirically detailed simulation models appropriate for scenario and policy analysis. We also discuss the challenge of validation and verification for MAS/LUCC models. Finally, we outline important challenges and open research questions in this new field. We conclude that, while significant challenges exist, these models offer a promising new tool for researchers whose goal is to create fine-scale models of LUCC phenomena that focus on humanenvironment interactions.
Bibliographical noteFunding Information:
This article has benefited from in-depth discussions with and comments from members of the Center for the Study of Institutions, Population, and Environmental Change (CIPEC) biocomplexity project at Indiana University, participants in the 2001 Special Workshop on agent-based models of land use, Elinor Ostrom, James Wilson, and five anonymous reviewers. All errors and omissions are the authors’ responsibility. The authors gratefully acknowledge financial support from the CIPEC through National Science Foundation (NSF) grants SBR9521918 and SES008351, the Resilience Alliance, the National Aeronautics and Space Administration (NASA) Earth System Science Fellowship program, the National Science Foundation (NSF) doctoral dissertation improvement grant 9907952, NASA’s LCLUC program (NAG 56406), and NSF grant 9521914 through the Carnegie Mellon University Center for Integrated Study of the Human Dimensions of Global Change.
- Agent-based modeling
- Cellular automata
- Complexity theory
- Land-use and land-cover change
- Multi-agent systems