Signals and boundaries : building blocks for complex adaptive systems /
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;...
Clasificación: | Libro Electrónico |
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Autor principal: | |
Formato: | Electrónico eBook |
Idioma: | Inglés |
Publicado: |
Cambridge, Mass. :
MIT Press,
©2012.
©2012 |
Temas: | |
Acceso en línea: | Texto completo |
MARC
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100 | 1 | |a Holland, John H. |q (John Henry), |d 1929-2015. | |
245 | 1 | 0 | |a Signals and boundaries : |b building blocks for complex adaptive systems / |c John H. Holland. |
260 | |a Cambridge, Mass. : |b MIT Press, |c ©2012. | ||
264 | 4 | |c ©2012 | |
300 | |a 1 online resource (viii, 308 pages) : |b illustrations | ||
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504 | |a Includes bibliographical references (pages 297-301) and index. | ||
588 | 0 | |a Print version record. | |
505 | 0 | |a Roles of signals and boundaries -- Theory and models: general principles -- Agents and signal processing -- Networks and flows -- Adaptation -- Recombination and reproduction -- Urn models of boundaries -- Boundary hierarchies -- The evolution of niches, a first look -- Language: grammars and niches -- Grammars as finitely generated systems -- An overarching signal/boundary framework -- A dynamic generated system model of ontogeny -- A complete dynamic generated system for signal/boundary studies -- Mathematical models of generated structures -- A short version of the whole. | |
520 | |a 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 | ||
546 | |a English. | ||
590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
650 | 0 | |a Adaptive control systems. | |
650 | 0 | |a Adaptation (Biology) |x Mathematical models. | |
650 | 0 | |a Signals and signaling |x Mathematical models. | |
650 | 6 | |a Systèmes adaptatifs. | |
650 | 6 | |a Adaptation (Biologie) |x Modèles mathématiques. | |
650 | 6 | |a Signaux et signalisation |x Modèles mathématiques. | |
650 | 7 | |a SCIENCE |x System Theory. |2 bisacsh | |
650 | 7 | |a TECHNOLOGY & ENGINEERING |x Operations Research. |2 bisacsh | |
650 | 7 | |a Adaptation (Biology) |x Mathematical models. |2 fast |0 (OCoLC)fst00796476 | |
650 | 7 | |a Adaptive control systems. |2 fast |0 (OCoLC)fst00796490 | |
650 | 7 | |a Signals and signaling |x Mathematical models. |2 fast |0 (OCoLC)fst01118313 | |
776 | 0 | 8 | |i Print version: |a Holland, John H. (John Henry), 1929-2015. |t Signals and boundaries. |d Cambridge, Mass. : MIT Press, ©2012 |z 9780262017831 |w (DLC) 2011052776 |w (OCoLC)775269168 |
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