Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology
V. Grimm
E. Revilla
U. Berger
F. Jeltsch
W. M. Mooij
S. F. Railsback
H.-H. Thulke
J. Weiner
T. Wiegand
D. L. DeAngelis
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.
Grimm V., Revilla E., Berger U., Jeltsch F., Mooij W.M., Railsback S.F., Thulke H.-H., Weiner J., Wiegand T. and DeAngelis D.L. (2005) Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology. Science 310(5750): 987-991. 10.1126/science.1116681
@article{Grimm2005,
Title = {Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology},
Author = {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.},
Editor = {},
Journal = {Science},
Year = {2005},
Pages = {987-991},
Volume = {310},
Doi = {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.},
}
TY - JOUR
AU - Grimm, V.
AU - Revilla, E.
AU - Berger, U.
AU - Jeltsch, F.
AU - Mooij, W. M.
AU - Railsback, S. F.
AU - Thulke, H.-H.
AU - Weiner, J.
AU - Wiegand, T.
AU - DeAngelis, D. L.
TI - Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology
T2 - Science
PY - 2005
SP - 987-991
VL - 310
DO - 10.1126/science.1116681
AB - 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.
ER -
