Swarm Intelligence
Institution of Engineering and Technology (Verlag)
978-1-78561-627-3 (ISBN)
Swarm Intelligence (SI) is one of the most important and challenging paradigms under the umbrella of computational intelligence. It focuses on the research of collective behaviours of a swarm in nature and/or social phenomenon to solve complicated and difficult problems which cannot be handled by traditional approaches. Thousands of papers are published each year presenting new algorithms, new improvements and numerous real world applications. This makes it hard for researchers and students to share their ideas with other colleagues; follow up the works from other researchers with common interests; and to follow new developments and innovative approaches. This complete and timely collection fills this gap by presenting the latest research systematically and thoroughly to provide readers with a full view of the field of swarm. Students will learn the principles and theories of typical swarm intelligence algorithms; scholars will be inspired with promising research directions; and practitioners will find suitable methods for their applications of interest along with useful instructions.
Volume 1 contains 20 chapters presenting the basic principles and current algorithms and methods of well-known swarm intelligence algorithms and efficient improvements from typical particle swarm optimization (PSO), ant colony optimization (ACO) and fireworks algorithm (FWA) as well as other swarm intelligence algorithms for swarm robotics.
With contributions from an international selection of leading researchers, Swarm Intelligence is essential reading for engineers, researchers, professionals and practitioners with interests in swarm intelligence.
Ying Tan is a full professor, PhD advisor, and director of the Computational Intelligence Laboratory at Peking University, China. He is also a professor at the Faculty of Design, Kyushu University, Japan. He serves as Editor-in-Chief of the International Journal of Computational Intelligence and Pattern Recognition (IJCIPR), and is Associate Editor of IEEE Transactions on Evolutionary Computation (TEC), IEEE Transactions on Cybernetics (CYB), IEEE Transactions on Neural Networks and Learning Systems (NNLS), International Journal of Swarm Intelligence Research (IJSIR), and International Journal of Artificial Intelligence (IJAI). He has been the founder general chair of the ICSI International Conference series since 2010, is the inventor of the Fireworks Algorithm (FWA), and has published extensively in this field.
Chapter 1: Survey of swarm intelligence
Chapter 2: Generalization ability of swarm intelligence algorithms
Chapter 3: A unifying framework for swarm intelligence-based hybrid algorithms
Chapter 4: Ant colony systems for optimization problems in dynamic environments
Chapter 5: Ant colony optimization for dynamic combinatorial optimization problems
Chapter 6: Comparison of multidimensional swarm embedding techniques by potential fields
Chapter 7: Inertia weight control strategies for PSO algorithms
Chapter 8: Robot path planning using swarms of active particles
Chapter 9: MAHM: a PSO-based multiagent architecture for hybridisation of metaheuristics
Chapter 10: The critical state in particle swarm optimisation
Chapter 11: Bounded distributed flocking control of nonholonomic mobile robots
Chapter 12: Swarming in forestry environments: collective exploration and network deployment
Chapter 13: Guiding swarm behavior by soft control
Chapter 14: Agreeing to disagree: synergies between particle swarm optimisation and complex networks
Chapter 15: Ant colony algorithms for the travelling salesman problem and the quadratic assignment problem
Chapter 16: A review of particle swarm optimization for multimodal problems
Chapter 17: Decentralized control in robotic swarms
Chapter 18: PSO in ANN, SVM and data clustering
Chapter 19: Modelling of interaction in swarm intelligence focused on particle swarm optimization and social networks optimization
Chapter 20: Coordinating swarms of microscopic agents to assemble complex structures
| Erscheinungsdatum | 05.12.2018 |
|---|---|
| Reihe/Serie | Control, Robotics and Sensors |
| Verlagsort | Stevenage |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Informatik ► Theorie / Studium ► Algorithmen | |
| Technik ► Elektrotechnik / Energietechnik | |
| ISBN-10 | 1-78561-627-7 / 1785616277 |
| ISBN-13 | 978-1-78561-627-3 / 9781785616273 |
| Zustand | Neuware |
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