Signals and boundaries : building blocks for complex adaptive systems / John H. Holland.
2012
TJ217 .H644 2012eb
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Title
Signals and boundaries : building blocks for complex adaptive systems / John H. Holland.
ISBN
0262305895 (electronic bk.)
9780262305891 (electronic bk.)
9780262017831
0262017830
9780262525930 print
9780262305891 (electronic bk.)
9780262017831
0262017830
9780262525930 print
Publication Details
Cambridge, Mass. : MIT Press, ©2012.
Copyright
©2012
Language
English
Description
1 online resource (viii, 308 pages) : illustrations
Item Number
9786613806390
Call Number
TJ217 .H644 2012eb
Dewey Decimal Classification
003
Summary
Complex adaptive systems (cas), including ecosystems, governments, biological cells, and markets, are characterized by intricate hierarchical arrangements of boundaries and signals. In ecosystems, for example, niches act as semi-permeable boundaries, and smells and visual patterns serve as signals; governments have departmental hierarchies with memoranda acting as signals; and so it is with other cas. Despite a wealth of data and descriptions concerning different cas, there remain many unanswered questions about "steering" these systems. In Signals and Boundaries, John Holland argues that understanding the origin of the intricate signal/border hierarchies of these systems is the key to answering such questions. He develops an overarching framework for comparing and steering cas through the mechanisms that generate their signal/boundary hierarchies. Holland lays out a path for developing the framework that emphasizes agents, niches, theory, and mathematical models. He discusses, among other topics, theory construction; signal-processing agents; networks as representations of signal/boundary interaction; adaptation; recombination and reproduction; the use of tagged urn models (adapted from elementary probability theory) to represent boundary hierarchies; finitely generated systems as a way to tie the models examined into a single framework; the framework itself, illustrated by a simple finitely generated version of the development of a multi-celled organism; and Markov processes.
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Source of Description
OCLC-licensed vendor bibliographic record.
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