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-b...

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Bibliographic Details
Published in:Science (American Association for the Advancement of Science) 2005-11, Vol.310 (5750), p.987-991
Main Authors: Grimm, Volker, Revilla, Eloy, Berger, Uta, Jeltsch, Florian, Mooij, Wolf M, Railsback, Steven F, Thulke, Hans-Hermann, Weiner, Jacob, Wiegand, Thorsten, DeAngelis, Donald L
Format: Article
Language:English
Subjects:
Analysis
Animal and plant ecology
Animal, plant and microbial ecology
Animals
Behavior, Animal
Biological and medical sciences
Complex systems
Computer Simulation
Decision Support Techniques
Ecological modeling
Ecological research
Ecology
Ecosystem
Ecosystem models
Ecosystems
Fishes - physiology
Fundamental and applied biological sciences. Psychology
General aspects
Hydrological modeling
Investors
Methods
Modeling
Models, Biological
Models, Economic
Models, Theoretical
Multilevel models
Parametric models
Review
Scientific method
Spatial models
Synecology
Systems Theory
Trees
Uncertainty
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Summary: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.
ISSN:0036-8075
1095-9203
DOI:10.1126/science.1116681