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

Science
By: , and 

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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.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Pattern-oriented modeling of agent-based complex systems: Lessons from ecology
Series title Science
DOI 10.1126/science.1116681
Volume 310
Issue 5750
Year Published 2005
Language English
Publisher AAAS
Contributing office(s) Southeast Ecological Science Center
Description 5 p.
First page 987
Last page 991
Online Only (Y/N) N
Additional Online Files (Y/N) N