Understanding Complex Systems

By: Rolf P. Wurtz (Editor)

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Hardcover | 28 March 2008

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368 Pages

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23.5 x 15.5 x 3.18

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Organic Computing is a research field emerging around the conviction that problems of organization in complex systems in computer science, telecommunications, neurobiology, molecular biology, ethology, and possibly even sociology can be tackled scientifically in a unified way. From the computer science point of view, the apparent ease in which living systems solve computationally difficult problems makes it inevitable to adopt strategies observed in nature for creating information processing machinery. In this book, the major ideas behind Organic Computing are delineated, together with a sparse sample of computational projects undertaken in this new field. Biological metaphors include evolution, neural networks, gene-regulatory networks, networks of brain modules, hormone system, insect swarms, and ant colonies. Applications are as diverse as system design, optimization, artificial growth, task allocation, clustering, routing, face recognition, and sign language understanding.

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Published: 18th November 2010

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Introduction: Organic Computing	p. 1
The Organic Future of Information Technology	p. 7
Systems Engineering for Organic Computing: The Challenge of Shared Design and Control between OC Systems and their Human Engineers	p. 25
Controlled Emergence and Self-Organization	p. 81
Organic Computing and Complex Dynamical Systems - Conceptual Foundations and Interdisciplinary Perspectives	p. 105
Evolutionary Design of Emergent Behavior	p. 123
Genesis of Organic Computing Systems: Coupling Evolution and Learning	p. 141
Organically Grown Architectures: Creating Decentralized, Autonomous Systems by Embryomorphic Engineering	p. 167
Artificial Development	p. 201
Self-adaptive Worker-Helper Systems with Self-Organized Task Allocation	p. 221
Concepts for Self-Adaptive and Self-Healing Networked Embedded Systems	p. 241
An Artificial Hormone System for Self-Organizing Real-Time Task Allocation in Organic Middleware	p. 261
Bio-Inspired Networking - Self-Organizing Networked Embedded Systems	p. 285
Subspace Image Representation for Facial Expression Analysis and Face Recognition and its Relation to the Human Visual System	p. 303
Self-organized Evaluation of Dynamic Hand Gestures for Sign Language Recognition	p. 321
Index	p. 343
Table of Contents provided by Ingram. All Rights Reserved.

Understanding Complex Systems

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