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Measures of Complexity [electronic resource] : Proceedings of the Conference, Held in Rome September 30 – October 2, 1987 / edited by L. Peliti, A. Vulpiani.

Contributor(s): Material type: TextTextSeries: Lecture Notes in Physics ; 314Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 1988Description: VII, 151 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540459682
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 530.1 23
LOC classification:
  • QC19.2-20.85
Online resources:
Contents:
Complexity and forecasting in dynamical systems -- On Complexity -- Boolean networks which learn to compute -- A dynamical learning process for the recognition of correlated patterns in symmetric spin glass models -- Neural networks that learn temporal sequences -- Hierarchical diffusion -- Random walks, random surfaces, and complexity -- Complexity in large technological systems -- An introduction to the theory of computational complexity -- Measures of biologically meaningful complexity -- Complex systems, organization and networks of automata -- Complexity in ecological systems.
In: Springer eBooksSummary: Complexity is a puzzling and important concept in contemporary research in many disciplines. This book addresses the problem of defining complexity by carefully analysing in what sense complexity means measure in such areas as the theory of dynamical systems, condensed matter physics, ecology, immunology and the theory of neural networks. The information content of complexity is studied and similarities and differences in the various concepts of complexity are highlighted, sometimes provocatively. The book could open the way to finding a paradigm of complexity, and should become a standard reference for a wide audience of researchers in the physical and biological sciences.
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Complexity and forecasting in dynamical systems -- On Complexity -- Boolean networks which learn to compute -- A dynamical learning process for the recognition of correlated patterns in symmetric spin glass models -- Neural networks that learn temporal sequences -- Hierarchical diffusion -- Random walks, random surfaces, and complexity -- Complexity in large technological systems -- An introduction to the theory of computational complexity -- Measures of biologically meaningful complexity -- Complex systems, organization and networks of automata -- Complexity in ecological systems.

Complexity is a puzzling and important concept in contemporary research in many disciplines. This book addresses the problem of defining complexity by carefully analysing in what sense complexity means measure in such areas as the theory of dynamical systems, condensed matter physics, ecology, immunology and the theory of neural networks. The information content of complexity is studied and similarities and differences in the various concepts of complexity are highlighted, sometimes provocatively. The book could open the way to finding a paradigm of complexity, and should become a standard reference for a wide audience of researchers in the physical and biological sciences.

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