Studying Complex Adaptive Systems
Abstract
Complex adaptive systems (cas) – systems that involve many components that adapt or learn as they interact – are at the heart of important contemporary problems. The study of cas poses unique challenges: Some of our most powerful mathematical tools, particularly methods involving fixed points, attractors, and the like, are of limited help in understanding the development of cas. This paper suggests ways to modify research methods and tools, with an emphasis on the role of computer-based models, to increase our understanding of cas.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41486/1/11424_2006_Article_1.pd- Article
- Economics / Management Science
- Systems Theory, Control
- Mathematical Modeling and Industrial Mathematics
- Probability Theory and Stochastic Processes
- Appl.Mathematics/Computational Methods of Engineering
- Industrial and Production Engineering
- Operations Research/Decision Theory
- Agent-based Systems
- Classifier Systems
- Complex Adaptive Systems
- Computer-based Models
- Credit Assignment
- Genetic Algorithms
- Parallelism
- Rule Discovery
- Signal-passing
- Tags
- Industrial and Operations Engineering
- Engineering
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Last time updated on 25/05/2012
This paper was published in Deep Blue Documents at the University of Michigan.
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