Pattern-oriented modeling of agent-based complex systems: Lessons from ecology
Links
- More information: Publisher Index Page (via DOI)
- Open Access Version: External Repository
- Download citation as: RIS | Dublin Core
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.
| 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 |
| Google Analytic Metrics | Metrics page |