Self-Organization, Emerging Properties, and Learning

. Ed(s): Babloyantz, Agnessa

ISBN 10: 1461366844 / ISBN 13: 9781461366843

Editore: Springer-Verlag New York Inc., 2012

Riguardo questo articolo

Proceedings of a NATO ARW held in Austin, Texas, March 12--14, 1990 Editor(s): Babloyantz, Agnessa. Series: NATO Science Series B. Num Pages: 319 pages, biography. BIC Classification: PHU; PSA. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 18. Weight in Grams: 504. . 2012. Softcover reprint of the original 1st ed. 1991. Paperback. . . . . Books ship from the US and Ireland.

Codice articolo V9781461366843

Dati bibliografici

• Titolo: Self-Organization, Emerging Properties, and Learning
• Editore: Springer-Verlag New York Inc.
• Data di pubblicazione: 2012
• Lingua: Inglese
• ISBN 10: 1461366844
• ISBN 13: 9781461366843
• Rilegatura: Brossura
• Condizione: New

Descrizione articolo

Riassunto

This volume contains the proceedings of the workshop held in March 1990 at Austin, Texas on Self-Organization, Emerging Properties and Learning. The workshop was co-sponsored by NATO Scientific Affairs Division, Solvay Institutes of Physics and Chemistry, the University of Texas at Austin and IC2 Institute at Austin. It gathered representatives from a large spectrum of scientific endeavour. The subject matter of self-organization extends over several fields such as hydrodynamics, chemistry, biology, neural networks and social sciences. Several key concepts are common to all these different disciplines. In general the self-organization processes in these fields are described in the framework of the nonlinear dynamics, which also governs the mechanisms underlying the learning processes. Because of this common language, it is expected that any progress in one area could benefit other fields, thus a beneficial cross fertilization may result. In last two decades many workshops and conferences had been organized in various specific fields dealing with self-organization and emerging properties of systems. The aim of the workshop in Austin was to bring together researchers from seemingly unrelated areas and interested in self-organization, emerg{ng properties and learning capabilities of interconnected multi-unit systems. The hope was to initiate interesting exchange and lively discussions. The expectations of the organiziers are materialized in this unusual collection of papers, which brings together in a single volume representative research from many related fields. Thus this volume gives to the reader a wider perspective over the generality and ramifications of the key concepts of self­ organization.

Contenuti

Spatio-Temporal Patterns and Network Computation.- Application of Synergetics to Pattern Information and Pattern Recognition.- Coupled Map Lattices : Abstract Dynamics and Models for Physical Systems.- The Self-Organized Phase Attractive Dynamics of Coordination.- Possible Neural Mechanisms of Feature Linking in the Visual System : Stimulus-Locked and Stimulus-Induced Synchronizations.- A Model for Synchronous Activity in the Visual Cortex.- Some Collective Phenomena in the Hippocampus In Vitro.- Information Theory and Early Visual Information Processing.- Deterministic Chaos in a Model of the Thalamo-cortical System.- Chaos and Information Processing: Multifractal Attractors Mediating Perception and Cognition.- Spontaneous Activity in a Large Neural Net: Between Chaos and Noise.- Neural Learning Algorithms and their Applications in Robotics.- Self-Organization of Spatial Representation and Arm Trajectory Controllers by Vector Associative Maps Energized by Cyclic Random Generators.- Neural Darwinism and Selective Recognition Automata: How Selection Shapes Perceptual Categories.- Asymptotic Behaviour of Neural Networks and Image Processing.- Entropy and Learning.- Molecular Evolution as a Complex Optimization Problem.- A Nonthermodynamic Formalism for Biological Information Systems: Hierarchical Lacunarity in Partition Size of Intermittency.- Collectively Self-Solving Problems.- Imitation, Learning, and Communication: Central or Polarized Patterns in Collective Actions.- Spectral Entropy as a Measure of Self-Organization in Transition Flows.- Contributors.