Swarm Intelligence An Approach from Natural to Artificial 1st Edition by Kuldeep Singh Kaswan, Jagjit Singh Dhatterwal, Avadhesh Kumar ISBN 9781119865551 1119865557

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Product details:

ISBN 10: 1119865557
ISBN 13: 9781119865551
Author: Kuldeep Singh Kaswan, Jagjit Singh Dhatterwal, Avadhesh Kumar

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.

Swarm Intelligence An Approach from Natural to Artificial 1st Edition Table of contents:

1 Introduction of Swarm Intelligence

1.1 Introduction to Swarm Behavior

1.2 Concepts of Swarm Intelligence

1.3 Particle Swarm Optimization (PSO)

1.4 Meaning of Swarm Intelligence

1.5 What Is Swarm Intelligence?

1.6 History of Swarm Intelligence

1.7 Taxonomy of Swarm Intelligence

1.8 Properties of Swarm Intelligence

1.9 Design Patterns in Cyborg Swarm

1.10 Design Patterns Updating in Cyborg

1.11 Property of Design Cyborg

1.12 Extending the Design of Cyborg

1.13 Bee-Inspired Cyborg

1.14 Conclusion

2 Foundation of Swarm Intelligence

2.1 Introduction

2.2 Concepts of Life and Intelligence

2.3 Symbols, Connections, and Optimization by Trial and Error

2.4 The Social Organism

2.5 Evolutionary Computation Theory and Paradigms

2.6 Humans – Actual, Imagined, and Implied

2.7 Thinking is Social

2.8 Conclusion

3 The Particle Swarm and Collective Intelligence

3.1 The Particle Swarm and Collective Intelligence

3.2 Variations and Comparisons

3.3 Implications and Speculations

3.4 Conclusion

4 Algorithm of Swarm Intelligence

4.1 Introduction

4.2 Ant Colony Algorithm

4.3 Artificial Bee Colony Optimization

4.4 Cat Swarm Optimization

4.5 Crow Search Optimization

4.6 Elephant Intelligent Behavior

4.7 Grasshopper Optimization

4.8 Conclusion

5 Novel Swarm Intelligence Optimization Algorithm (SIOA)

5.1 Water Wave Optimization

5.2 Brain Storm Optimization

5.3 Whale Optimization Algorithm

5.4 Conclusion

6 Swarm Cyborg

6.1 Introduction

6.2 Swarm Cyborg Taxis Algorithms

6.3 Swarm Intelligence Approaches to Swarm Cyborg

6.4 Swarm Cyborg Applications

6.5 Conclusion

7 Immune-Inspired Swarm Cybernetic Systems

7.1 Introduction

7.2 Reflections on the Development of Immune-Inspired Solution for Swarm Cybernetic Systems

7.3 Cyborg Static Environment

7.4 Cyborg Swarm Performance

7.5 Information Flow Analysis in Cyborgs

7.6 Cost Analysis of Cyborgs

7.7 Cyborg Swarm Environment

7.8 Conclusion

8 Application of Swarm Intelligence

8.1 Swarm Intelligence Robotics

8.2 An Agent-Based Approach to Self-Organized Production

8.3 Organic Computing and Swarm Intelligence

8.4 Swarm Intelligence Techniques for Cloud Services

8.5 Routing Protocols for Next-Generation Networks Inspired by Collective Behaviors of Insect Societies

8.6 Swarm Intelligence in Data Mining

8.7 Swarm Intelligence and Knowledge Discovery

8.8 Ant Colony Optimization and Data Mining

8.9 Conclusion

References

Index

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Kuldeep Singh Kaswan,Jagjit Singh Dhatterwal,Avadhesh Kumar,Swarm Intelligence,Artificial