Swarm Intelligence

Book description

SWARM INTELLIGENCE

This important authored book presents valuable new insights by exploring the boundaries shared by cognitive science, social psychology, artificial life, artificial intelligence, and evolutionary computation by applying these insights to solving complex engineering problems.

Motivated by the capability of the biologically inspired algorithms, “Swarm Intelligence: An Approach from Natural to Artificial” focuses on ant, cat, crow, elephant, grasshopper, water wave and whale optimization, swarm cyborg and particle swarm optimization, and presents recent developments and applications concerning optimization with swarm intelligence techniques. The goal of the book is to offer a wide spectrum of sample works developed in leading research throughout the world about innovative methodologies of swarm intelligence and foundations of engineering swarm intelligent systems; as well as applications and interesting experiences using particle swarm optimization, which is at the heart of computational intelligence.

Discussed in the book are applications of various swarm intelligence models to operational planning of energy plants, modeling, and control of robots, organic computing, techniques of cloud services, bioinspired optimization, routing protocols for next-generation networks inspired by collective behaviors of insect societies and cybernetic organisms.

Audience

The book is directed to researchers, practicing engineers, and students in computational intelligence who are interested in enhancing their knowledge of techniques and swarm intelligence.

Table of contents

  1. Cover
  2. Series Page
  3. Title Page
  4. Copyright Page
  5. Preface
  6. 1 Introduction of Swarm Intelligence
    1. 1.1 Introduction to Swarm Behavior
    2. 1.2 Concepts of Swarm Intelligence
    3. 1.3 Particle Swarm Optimization (PSO)
    4. 1.4 Meaning of Swarm Intelligence
    5. 1.5 What Is Swarm Intelligence?
    6. 1.6 History of Swarm Intelligence
    7. 1.7 Taxonomy of Swarm Intelligence
    8. 1.8 Properties of Swarm Intelligence
    9. 1.9 Design Patterns in Cyborg Swarm
    10. 1.10 Design Patterns Updating in Cyborg
    11. 1.11 Property of Design Cyborg
    12. 1.12 Extending the Design of Cyborg
    13. 1.13 Bee-Inspired Cyborg
    14. 1.14 Conclusion
  7. 2 Foundation of Swarm Intelligence
    1. 2.1 Introduction
    2. 2.2 Concepts of Life and Intelligence
    3. 2.3 Symbols, Connections, and Optimization by Trial and Error
    4. 2.4 The Social Organism
    5. 2.5 Evolutionary Computation Theory and Paradigms
    6. 2.6 Humans – Actual, Imagined, and Implied
    7. 2.7 Thinking is Social
    8. 2.8 Conclusion
  8. 3 The Particle Swarm and Collective Intelligence
    1. 3.1 The Particle Swarm and Collective Intelligence
    2. 3.2 Variations and Comparisons
    3. 3.3 Implications and Speculations
    4. 3.4 Conclusion
  9. 4 Algorithm of Swarm Intelligence
    1. 4.1 Introduction
    2. 4.2 Ant Colony Algorithm
    3. 4.3 Artificial Bee Colony Optimization
    4. 4.4 Cat Swarm Optimization
    5. 4.5 Crow Search Optimization
    6. 4.6 Elephant Intelligent Behavior
    7. 4.7 Grasshopper Optimization
    8. 4.8 Conclusion
  10. 5 Novel Swarm Intelligence Optimization Algorithm (SIOA)
    1. 5.1 Water Wave Optimization
    2. 5.2 Brain Storm Optimization
    3. 5.3 Whale Optimization Algorithm
    4. 5.4 Conclusion
  11. 6 Swarm Cyborg
    1. 6.1 Introduction
    2. 6.2 Swarm Cyborg Taxis Algorithms
    3. 6.3 Swarm Intelligence Approaches to Swarm Cyborg
    4. 6.4 Swarm Cyborg Applications
    5. 6.5 Conclusion
  12. 7 Immune-Inspired Swarm Cybernetic Systems
    1. 7.1 Introduction
    2. 7.2 Reflections on the Development of Immune-Inspired Solution for Swarm Cybernetic Systems
    3. 7.3 Cyborg Static Environment
    4. 7.4 Cyborg Swarm Performance
    5. 7.5 Information Flow Analysis in Cyborgs
    6. 7.6 Cost Analysis of Cyborgs
    7. 7.7 Cyborg Swarm Environment
    8. 7.8 Conclusion
  13. 8 Application of Swarm Intelligence
    1. 8.1 Swarm Intelligence Robotics
    2. 8.2 An Agent-Based Approach to Self-Organized Production
    3. 8.3 Organic Computing and Swarm Intelligence
    4. 8.4 Swarm Intelligence Techniques for Cloud Services
    5. 8.5 Routing Protocols for Next-Generation Networks Inspired by Collective Behaviors of Insect Societies
    6. 8.6 Swarm Intelligence in Data Mining
    7. 8.7 Swarm Intelligence and Knowledge Discovery
    8. 8.8 Ant Colony Optimization and Data Mining
    9. 8.9 Conclusion
  14. References
  15. Index
  16. End User License Agreement

Product information

  • Title: Swarm Intelligence
  • Author(s): Kuldeep Singh Kaswan, Jagjit Singh Dhatterwal, Avadhesh Kumar
  • Release date: March 2023
  • Publisher(s): Wiley-Scrivener
  • ISBN: 9781119865063