Agent-Based Modeling and Complexity

Steven M. Mason, Shiping Sun, Dudley Bonsal

Research output: Chapter in Book/Report/Conference proceedingChapter

24 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationAgent-Based Models of Geographical Systems
EditorsA. Heppenstall, A. Crooks, L. See, M. Batty
Place of PublicationBerlin, Germany
PublisherSpringer Netherlands
Pages125-139
Number of pages15
ISBN (Print)9789048189274, 9789048189267
DOIs
StatePublished - Jan 1 2012

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    Mason, S. M., Sun, S., & Bonsal, D. (2012). Agent-Based Modeling and Complexity. In A. Heppenstall, A. Crooks, L. See, & M. Batty (Eds.), Agent-Based Models of Geographical Systems (pp. 125-139). Springer Netherlands. https://doi.org/10.1007/978-90-481-8927-4_7