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Advances in Evolutionary Computing for System Design

  • Book
  • © 2007

Overview

  • Latest research on the evolution of intelligent systems and their applications
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Computational Intelligence (SCI, volume 66)

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Table of contents (13 chapters)

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About this book

Evolutionary computing paradigms offer robust and powerful adaptive search mechanisms for system design. This book includes thirteen chapters covering a wide area of topics in evolutionary computing and applications including: Introduction to evolutionary computing in system design; evolutionary neuro-fuzzy systems; evolution of fuzzy controllers; genetic algorithms for multi-classifier design; evolutionary grooming of traffic; evolutionary particle swarms; fuzzy logic systems using genetic algorithms; evolutionary algorithms and immune learning for neural network-based controller design; distributed problem solving using evolutionary learning; evolutionary computing within grid environment; evolutionary game theory in wireless mesh networks; hybrid multiobjective evolutionary algorithms for the sailor assignment problem; evolutionary techniques in hardware optimization. This book will be useful to researchers in intelligent systems with interest in evolutionary computing, application engineers and system designers. The book can also be used by students and lecturers as an advanced reading material for courses on evolutionary computing.

Editors and Affiliations

  • University of South Australia, South Australia, Australia

    Lakhmi C. Jain

  • Computing Laboratory, Oxford, England

    Vasile Palade

  • National University of Singapore, Singapore

    Dipti Srinivasan

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