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

TitlePattern-oriented modeling of agent-based complex systems: lessons from ecology.
Publication TypeMagazine Article
Year of Publication2005
AuthorsGrimm, V, Revilla, E, Berger, U, Jeltsch, F, Mooij, WM, Railsback, SF, Thulke, H-H, Weiner, J, Wiegand, T, DeAngelis, DL
Date Published2005/11/11/
ISBN Number0036-8075
KeywordsAnalysis, Ecological research_Analysis, Ecological research_Methods, Methods

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.