Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology.
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). pp. 987-991. DOI https://doi.org/10.1126/science.1116681.
Full text not available from this repository.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.
Document Type: | Article |
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Programme Area: | UNSPECIFIED |
Research affiliation: | Ecology > Mangrove Ecology |
Refereed: | Yes |
Open Access Journal?: | No |
DOI: | https://doi.org/10.1126/science.1116681 |
ISSN: | 0036-8075 |
Date Deposited: | 16 Mar 2020 11:11 |
Last Modified: | 26 Mar 2024 13:30 |
URI: | http://cris.leibniz-zmt.de/id/eprint/3635 |
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