LNAI 4335 Engineering Self Organising Systems 4th edition by Sven Brueckner, Salima Hassas, Márk Jelasity, Daniel Yamins ISBN 3540698671 978-3540698678

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ISBN 10: 3540698671
ISBN 13: 978-3540698678
Author: Sven Brueckner, Salima Hassas, Márk Jelasity, Daniel Yamins

This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Engineering Self-Organising Applications, ESOA 2006, held in Hakodate, Japan in May 2006. This was an associated event of AAMAS 2006, the 5th International Joint Conference on Autonomous Agents and Multi-Agent Systems. The seven full papers presented together with six invited papers were carefully selected for inclusion in the book.

LNAI 4335 – Engineering Self-Organising Systems 4th Table of contents:

Preface

• Overview of the Book
• Objectives and Goals
• Structure of the Book
• Acknowledgments

Chapter 1: Introduction to Self-Organising Systems

• Defining Self-Organising Systems
• Key Concepts in Self-Organization
• The Role of Self-Organising Systems in Engineering
• Applications in Nature and Engineering

Chapter 2: Theoretical Foundations of Self-Organization

• Complexity Theory and Self-Organization
• Emergent Behaviors in Systems
• Dynamical Systems and Nonlinear Dynamics
• Stability and Attractors in Self-Organising Systems

Chapter 3: Modeling Self-Organising Systems

• Mathematical Models of Self-Organising Systems
• Cellular Automata and Agent-Based Models
• The Role of Feedback Loops
• Simulation of Self-Organising Systems

Chapter 4: Algorithms for Self-Organisation

• Distributed Algorithms for Self-Organisation
• Consensus and Coordination in Multi-Agent Systems
• Evolutionary Algorithms and Genetic Programming
• Swarm Intelligence and Particle Swarm Optimization

Chapter 5: Engineering Applications of Self-Organising Systems

• Self-Organising Systems in Robotics
• Application in Autonomous Vehicles
• Self-Healing Materials and Systems
• Network Design and Optimization

Chapter 6: Learning and Adaptation in Self-Organising Systems

• Machine Learning Approaches for Self-Organization
• Reinforcement Learning and Self-Adaptation
• Artificial Neural Networks and Evolutionary Algorithms
• Adaptive Systems in Real-World Applications

Chapter 7: Self-Organisation in Distributed Systems

• Self-Organising Networks
• Decentralized Control in Distributed Systems
• Fault Tolerance and Robustness in Self-Organising Systems
• Case Studies of Distributed Self-Organising Systems

Chapter 8: Challenges in Engineering Self-Organising Systems

• Designing Stable and Scalable Systems
• Managing Complexity in Self-Organising Systems
• Addressing Uncertainty and Nonlinearity
• Ethical and Practical Challenges in System Design

Chapter 9: Future Directions in Self-Organising Systems

• Emerging Trends in Self-Organising Technologies
• Integration with Internet of Things (IoT) and Smart Systems
• The Role of AI and Machine Learning in Future Self-Organising Systems
• The Potential of Self-Organising Systems in Industry 4.0

Chapter 10: Case Studies and Applications

• Case Study 1: Self-Organising Systems in Manufacturing
• Case Study 2: Self-Organising Algorithms in Communication Networks
• Case Study 3: Self-Healing Systems in Aerospace Engineering
• Lessons Learned and Best Practices

Index

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