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Swarm Intelligent Systems

  • Book
  • © 2006

Overview

Editors:
  1. Nadia Nedjah

    1. Department of Electronics Engineering and Telecommunications - DETEL, Faculty of Engineering - FEN, State University of Rio de Janeiro - UERJ, Maracanã, Brazil

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  2. Luiza de Macedo Mourelle

    1. Department of Electronics Engineering and Telecommunications - DESC, Faculty of Engineering - FEN, State University of Rio de Janeiro - UERJ, Maracanã, Brazil

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  • Recent advances in swarm intelligence and cooperative behaviour

Part of the book series: Studies in Computational Intelligence (SCI, volume 26)

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Table of contents (8 chapters)

  1. Front Matter

    Pages I-XX
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  2. Methodologies Based on Particle Swarm Intelligence

    1. Front Matter

      Pages 1-1
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    2. Swarm Intelligence: Foundations, Perspectives and Applications

      • Ajith Abraham, He Guo, Hongbo Liu
      Pages 3-25

    3. Waves of Swarm Particles (WoSP)

      • Tim Hendtlass
      Pages 27-58

    4. Grammatical Swarm: A Variable-Length Particle Swarm Algorithm

      • Michael O'Neill, Finbar Leahy, Anthony Brabazon
      Pages 59-74

    5. SWARMs of Self-Organizing Polymorphic Agents

      • Derek Messie, Jae C. Oh
      Pages 75-90

  3. Experiences Using Particle Swarm Intelligence

    1. Front Matter

      Pages 92-92
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    2. Swarm Intelligence — Searchers, Cleaners and Hunters

      • Yaniv Altshuler, Vladimir Yanovsky, Israel A. Wagner, Alfred M. Bruckstein
      Pages 93-132

    3. Ant Colony Optimisation for Fast Modular Exponentiation using the Sliding Window Method

      • Nadia Nedjah, Luiza de Macedo Mourelle
      Pages 133-147

    4. Particle Swarm for Fuzzy Models Identification

      • Arun Khosla, Shakti Kumar, K. K. Aggarwal, Jagatpreet Singh
      Pages 149-173

    5. A Matlab Implementation of Swarm Intelligence based Methodology for Identification of Optimized Fuzzy Models

      • Arun Khosla, Shakti Kumar, K. K. Aggarwal, Jagatpreet Singh
      Pages 175-184

  4. Back Matter

    Pages 185-185
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Keywords

About this book

Swarm intelligence is an innovative computational way to solving hard pr- lems. This discipline is inspired by the behavior of social insects such as ?sh schools and bird ?ocks and colonies of ants, termites, bees and wasps. In g- eral, this is done by mimicking the behavior of the biological creatures within their swarms and colonies. Particle swarm optimization, also commonly known as PSO, mimics the behaviorofaswarmofinsectsoraschoolof?sh.Ifoneoftheparticlediscovers a good path to food the rest of the swarm will be able to follow instantly even if they are far away in the swarm. Swarm behavior is modeled by particles in multidimensionalspacethathavetwocharacteristics:apositionandavelocity. Theseparticleswanderaroundthehyperspaceandrememberthebestposition that they have discovered. They communicate good positions to each other and adjust their own position and velocity based on these good positions. The ant colony optimization, commonly known as ACO, is a probabilistic technique for solving computational hard problems which can be reduced to ?ndingoptimalpaths.ACOisinspiredbythebehaviorofantsin?ndingshort paths from the colony nest to the food place. Ants have small brains and bad vision yet they use great search strategy. Initially, real ants wander randomly to ?nd food. They return to their colony while laying down pheromone trails. If other ants ?nd such a path, they are likely to follow the trail with some pheromone and deposit more pheromone if they eventually ?nd food.

Editors and Affiliations

  • Department of Electronics Engineering and Telecommunications - DETEL, Faculty of Engineering - FEN, State University of Rio de Janeiro - UERJ, Maracanã, Brazil

    Nadia Nedjah

  • Department of Electronics Engineering and Telecommunications - DESC, Faculty of Engineering - FEN, State University of Rio de Janeiro - UERJ, Maracanã, Brazil

    Luiza de Macedo Mourelle

Bibliographic Information

  • Book Title: Swarm Intelligent Systems

  • Editors: Nadia Nedjah, Luiza de Macedo Mourelle

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-540-33869-7

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2006

  • Hardcover ISBN: 978-3-540-33868-0Published: 27 June 2006

  • Softcover ISBN: 978-3-642-07041-9Published: 25 November 2010

  • eBook ISBN: 978-3-540-33869-7Published: 22 November 2006

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XX, 184

  • Topics: Mathematical and Computational Engineering, Artificial Intelligence

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