Studying Complex Adaptive Systems
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.
Key WordsAgent-based systems classifier systems complex adaptive systems computer-based models credit assignment genetic algorithms parallelism rule discovery signal-passing tags
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