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03769nam a2200541 4500 |
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978-3-030-02589-2 |
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20191024214154.0 |
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190213s2019 gw | s |||| 0|eng d |
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|a 9783030025892
|9 978-3-030-02589-2
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|a 10.1007/978-3-030-02589-2
|2 doi
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|a QA267.7
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|a 620
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|a Tranquillo, Joe.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a An Introduction to Complex Systems
|h [electronic resource] :
|b Making Sense of a Changing World /
|c by Joe Tranquillo.
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250 |
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|a 1st ed. 2019.
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264 |
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2019.
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300 |
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|a XIV, 396 p. 121 illus., 12 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a text file
|b PDF
|2 rda
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|a Introduction -- Simple Rules - Complex Behavior -- Non-linear Systems -- Pattern Formation -- Networks -- Information Flow -- Thermodynamics of Complex Systems -- Game Theory -- Dynamics on Networks -- The Edge -- Criticisms and Future Work.
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520 |
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|a This book explores the interdisciplinary field of complex systems theory. By the end of the book, readers will be able to understand terminology that is used in complex systems and how they are related to one another; see the patterns of complex systems in practical examples; map current topics, in a variety of fields, to complexity theory; and be able to read more advanced literature in the field. The book begins with basic systems concepts and moves on to how these simple rules can lead to complex behavior. The author then introduces non-linear systems, followed by pattern formation, and networks and information flow in systems. Later chapters cover the thermodynamics of complex systems, dynamical patterns that arise in networks, and how game theory can serve as a framework for decision making. The text is interspersed with both philosophical and quantitative arguments, and each chapter ends with questions and prompts that help readers make more connections. Studies the tools of complex system theory that include chaos and fractals, game theory, networks, agent-based models and information theory; Contains examples, some outside the traditional boundaries of science, to help build a more intuitive feeling for complex systems; Outlines principles that can be used to design the next generation of machines and automata.
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650 |
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|a Computational complexity.
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650 |
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|a Statistical physics.
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650 |
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|a Dynamical systems.
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650 |
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|a Applied mathematics.
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650 |
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|a Engineering mathematics.
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650 |
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|a Systems biology.
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650 |
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|a Artificial intelligence.
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650 |
1 |
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|a Complexity.
|0 http://scigraph.springernature.com/things/product-market-codes/T11022
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650 |
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|a Complex Systems.
|0 http://scigraph.springernature.com/things/product-market-codes/P33000
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650 |
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|a Applications of Mathematics.
|0 http://scigraph.springernature.com/things/product-market-codes/M13003
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650 |
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|a Systems Biology.
|0 http://scigraph.springernature.com/things/product-market-codes/L15010
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650 |
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|a Artificial Intelligence.
|0 http://scigraph.springernature.com/things/product-market-codes/I21000
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710 |
2 |
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|a SpringerLink (Online service)
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773 |
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|t Springer eBooks
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776 |
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|i Printed edition:
|z 9783030025885
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776 |
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|i Printed edition:
|z 9783030025908
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856 |
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|u https://doi.org/10.1007/978-3-030-02589-2
|z Full Text via HEAL-Link
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912 |
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|a ZDB-2-ENG
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950 |
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|a Engineering (Springer-11647)
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