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Pattern-oriented modeling of agent-based complex systems: lessons from ecology.
- Source :
-
Science (New York, N.Y.) [Science] 2005 Nov 11; Vol. 310 (5750), pp. 987-91. - Publication Year :
- 2005
-
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.
Details
- Language :
- English
- ISSN :
- 1095-9203
- Volume :
- 310
- Issue :
- 5750
- Database :
- MEDLINE
- Journal :
- Science (New York, N.Y.)
- Publication Type :
- Academic Journal
- Accession number :
- 16284171
- Full Text :
- https://doi.org/10.1126/science.1116681