AI and swarm [Book] : evolutionary approach to emergent intelligence / Hitoshi Iba.

By:

Iba, Hitoshi [author.]

Material type: Text

TextDescription: xii, 238 pages : illustrations (black and white, and color) ; 24 cmISBN:

9780367136314 (hardback)

DDC classification:

006.3 23

Other classification:

006.3

Summary: This book provides theoretical and practical knowledge on AI and swarm intelligence. It provides a methodology for EA (evolutionary algorithm)-based approach for complex adaptive systems with the integration of several meta-heuristics, e.g., ACO (Ant Colony Optimization), ABC (Artificial Bee Colony), and PSO (Particle Swarm Optimization), etc. These developments contribute towards better problem-solving methodologies in AI. The book also covers emerging uses of swarm intelligence in applications such as complex adaptive systems, reaction-diffusion computing, and diffusion-limited aggregation, etc.

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Holdings
Item type	Current library	Call number	Status	Date due	Barcode	Item holds
Books	Junaid Zaidi Library, COMSATS University Islamabad Ground Floor	006.3 IBA-A 61261 (Browse shelf(Opens below))	Available		10001000061261

Total holds: 0

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Previous	006.3 HAY-N Neural networks a comprehensive foundation /	006.3 HAY-N Neural networks a comprehensive foundation /	006.3 HER-I Introduction to the theory of neural computation volume 1: lecture notes /	006.3 IBA-A 61261 AI and swarm evolutionary approach to emergent intelligence /	006.3 INT 62573 Intelligent computing methodologies 15th International Conference, ICIC 2019, Nanchang, China, August 3-6, 2019 : proceedings part III Part III /	006.3 JAC-I 62576 Introduction to artificial intelligence /	006.3 JAN-N Neuro-fuzzy and soft computing a computational approach to learning and machine intelligence /	Next

This book provides theoretical and practical knowledge on AI and swarm intelligence. It provides a methodology for EA (evolutionary algorithm)-based approach for complex adaptive systems with the integration of several meta-heuristics, e.g., ACO (Ant Colony Optimization), ABC (Artificial Bee Colony), and PSO (Particle Swarm Optimization), etc. These developments contribute towards better problem-solving methodologies in AI. The book also covers emerging uses of swarm intelligence in applications such as complex adaptive systems, reaction-diffusion computing, and diffusion-limited aggregation, etc.

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