Complex systems: Network thinking

被引:177
|
作者
Mitchell, Melanie [1 ]
机构
[1] Portland State Univ, Portland, OR 97207 USA
[2] Santa Fe Inst, Santa Fe, NM 87501 USA
关键词
complex systems; networks; small-world networks; scale-free networks; cellular automata; biologically inspired AI; information processing;
D O I
10.1016/j.artint.2006.10.002
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this article, I discuss some recent ideas in complex systems on the topic of networks, contained in or inspired by three recent complex systems books. The general science of networks is the subject of Albert-Lazlo Barabasi's Linked [A.-L. Barabasi, Linked: The New Science of Networks, Perseus, New York, 2002] and Duncan Watts' Six Degrees [D. Watts, Six Degrees: The Science of a Connected Age, Gardner's Books, New York, 2003]. Commonalities among complex biological networks, e.g., immune systems, social insects, and cellular metabolism, and their relation to intelligence in computational systems are explored in the proceedings of a interdisciplinary conference on "Distributed Autonomous Systems" [L.A. Segel, I.R. Cohen (Eds.), Design Principles for the Immune System and Other Distributed Autonomous Systems, Oxford University Press, New York, 2001]. The ideas discussed in the third book have led to me to propose four general principles of adaptive information processing in decentralized systems. These principles, and the relevance of "network thinking" for artificial intelligence (and vice versa), are the subject of the last two sections of the article. (C) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:1194 / 1212
页数:19
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