Chapter

Agent-Based Models of Geographical Systems

pp 125-139

Date:

Agent-Based Modeling and Complexity

  • Steven M. MansonAffiliated withDepartment of Geography, University of Minnesota Email author 
  • , Shipeng SunAffiliated withDepartment of Geography, University of Minnesota
  • , Dudley BonsalAffiliated withDepartment of Geography, University of Minnesota

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Abstract

Complexity theory provides a common language and rubric for applying agent-based processes to a range of complex systems. Agent-based modeling in turn advances complexity science by actuating many complex system characteristics, such as self-organization, nonlinearity, sensitivity, and resilience. There are many points of contact between complexity and agent-based modeling, and we examine several of particular importance: the range of complexity approaches; tensions between theoretical and empirical research; calibration, verification, and validation; scale; equilibrium and change; and decision making. These issues, together and separately, comprise some of the key issues found at the interface of complexity research and agent-based modeling.