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.
Grimm
Volker
V
UFZ Umweltforschungszentrum Leipzig-Halle, Department Okologische Systemanalyse, PF 500 136, 04301 Leipzig, Germany. volker.grimm@ufz.de
Revilla
Eloy
E
Berger
Uta
U
Jeltsch
Florian
F
Mooij
Wolf M
WM
Railsback
Steven F
SF
Thulke
Hans-Hermann
HH
Weiner
Jacob
J
Wiegand
Thorsten
T
DeAngelis
Donald L
DL
D000818:Animals; D001522:Behavior, Animal; D003661:Decision Support Techniques; D004463:Ecology; D017753:Ecosystem; D005399:Fishes / Q000502:physiology; D008954:Models, Biological; D018803:Models, Economic; D008962:Models, Theoretical; D013598:Systems Theory; D014197:Trees; D035501:Uncertainty