Pattern-oriented modeling of agent-based complex systems: Lessons from ecology
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.
Citation Information
Publication Year | 2005 |
---|---|
Title | Pattern-oriented modeling of agent-based complex systems: Lessons from ecology |
DOI | 10.1126/science.1116681 |
Authors | Volker Grimm, Eloy Revilla, Uta Berger, Florian Jeltsch, Wolf M. Mooij, Steven F. Railsback, Hans-Hermann Thulke, Jacob Weiner, Thorsten Wiegand, Donald L. DeAngelis |
Publication Type | Article |
Publication Subtype | Journal Article |
Series Title | Science |
Index ID | 70161783 |
Record Source | USGS Publications Warehouse |
USGS Organization | Southeast Ecological Science Center |