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

Grimm, V. and Revilla, E. and Berger, U. and Jeltsch, F. and Mooij, W.M. and Railsback, S.F. and Thulke, H-H. and Weiner, J. and Wiegand, T. and DeAngelis, D.L. (2005) Pattern-oriented modeling of agent-based complex systems: lessons from ecology. Science, 310, 987-991. ISSN 0036-8075.

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Official URL: http://dx.doi.org/10.1126/science.1116681

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.

Item Type:Article
Institutes:Nederlands Instituut voor Ecologie (NIOO)
ID Code:11716
Deposited On:23 Nov 2011 01:00
Last Modified:31 Mar 2014 10:46

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