@article {243, title = {Pattern-oriented modeling of agent-based complex systems: lessons from ecology.}, journal = {Science}, volume = {310}, year = {2005}, month = {2005/11/11/}, pages = {987(5)}, 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.

}, keywords = {Analysis, Ecological research_Analysis, Ecological research_Methods, Methods}, isbn = {0036-8075}, author = {Grimm,Volker and Revilla,Eloy and Berger,Uta and Jeltsch,Florian and Mooij, Wolf M. and Railsback, Steven F. and Thulke,Hans-Hermann and Weiner,Jacob and Wiegand,Thorsten and DeAngelis, Donald L.} }