Studying complex adaptive systems

被引：503

作者：

Holland J.H. ^{[1
]}

机构：

[1] Department of Electrical Engineering and Computer Science, College of Engineering, University of Michigan, Ann Arbor, MI 48109-2122

来源：

Journal of Systems Science and Complexity | 2006年 / 19卷 / 1期

关键词：

Agent-based systems; Classifier systems; Complex adaptive systems; Computer-based models; Credit assignment; Genetic algorithms; Parallelism; Rule discovery; Signal-passing; Tags;

D O I：

10.1007/s11424-006-0001-z

中图分类号：

学科分类号：

摘要：

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. © Springer Science + Business Media, Inc. 2006.

引用

页码：1 / 8

页数：7

共 12 条

[1]

Whitehead A.N., Russell B., Principia Mathematica, (1927)

[2]

Bull L., Kovacs T., Foundations of Learning Classifier Systems, (2005)

[3]

Lanzi P.L., Stolzmann W., Wilson S.W., Learning Classifier Systems, (2000)

[4]

Holland J.H., Holyoak K.J., Nisbett R.E., Thagard P.R., Induction: Processes of Inference, Learning, and Discovery (2nd Edition), pp. 71-75, (1989)

[5]

Booker L., Forrest S., Mitchell M., Riolo R., Perspectives on Adapatation in Natural and Artificial Systems, (2005)

[6]

Holland J.H., Hidden Order: How Adaptation Builds Complexity, (1995)

[7]

Bull L., Applications of Learning Classifier Systems, (2004)

[8]

Von Neumann J., Theory of Self-reproducing Automata, (1966)

[9]

Holland J.H., Hidden Order: How Adaptation Builds Complexity, (1995)

[10]

Odling-Smee F.J., Laland K.N., Feldman M.W., Niche Construction: The Neglected Process in Evolution, (2003)

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