Pattern-oriented modeling of agent-based complex systems: lessons from ecology

V. Grimm, E. Revilla, U. Berger, F. Jeltsch, W.M. Mooij, S.F. Railsback, H-H. Thulke, J. Weiner, T. Wiegand, D.L. DeAngelis

Research output: Contribution to journal/periodicalArticleScientificpeer-review

Abstract

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.
Original languageEnglish
Pages (from-to)987-991
JournalScience Magazine
Volume310
Issue number5750
DOIs
Publication statusPublished - 2005

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    Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W. M., Railsback, S. F., Thulke, H-H., Weiner, J., Wiegand, T., & DeAngelis, D. L. (2005). Pattern-oriented modeling of agent-based complex systems: lessons from ecology. Science Magazine, 310(5750), 987-991. https://doi.org/10.1126/science.1116681