Applied Swarm Intelligence / Edition 1

by Yaniv Altshuler

Overview

This book offers a comprehensive analysis of the variety of tools and techniques used today for the design and modeling of efficient and robust swarm-intelligence based systems: highly (or fully) decentralized, semi-autonomous, highly-scalable infrastructures in various real-life scenarios. Among others, the book reviews the use of the swarm intelligence paradigm in financial investment, blockchain protocols design, shared transportation systems, communication networks, and military applications. Theoretical and practical limitations of such systems are discussed, as well as trade-offs between the various economic and operational parameters of the systems. The book is intended for researchers and engineers in the fields of swarms systems, economics and operation research.

Key Features • Explains, in a detailed and clear way, the mathematical principles behind swarm intelligence • Illustrates how swarm intelligence can be used in real-world'systems • Reviews leading state-of-the-art approaches in the design and modeling of swarm systems today

Product Details

ISBN-13:	9780367226879
Publisher:	CRC Press
Publication date:	07/01/2024
Pages:	200
Product dimensions:	6.12(w) x 9.19(h) x (d)

About the Author

Dr. Altshuler is an expert on the mathematical aspects of networks and communities, and the way local interactions are translated to macro-scale behaviors. Altshuler graduated his BA and PhD (Computer Science) at the Israel Institute of Technology (Technion), followed by 3 years post-doc at MIT Media Lab. Published a book on Security and Privacy in Social Networks (2012), and a second one about Swarms and Network Intelligence (2017). Published over 60 scientific papers and 15 patents. His research was covered by Harvard Business Review, Financial Times, Communications of the ACM, The Globe, IEEE Spectrum and others. Together with Prof. Alex “Sandy” Pentland at MIT developed the new science of Social Physics.

Table of Contents

1. Introduction to applied swarm intelligence. 2. Ride sharing as a swarm – a dynamic network analysis approach. 3. Optimal coverage infrastructure for large-scale dynamic fleets of reconnaissance drones. 4. A swarm-based approach for modeling reliability and optimizing system maintenance. 5. On mice and financial traders – swarms as decision optimization mechanisms. 6. Complex crowds: on the interactions of the masses. 7. Predicting income based on twitter activity. 8. Efficient sub-linear algorithms for social networks analysis. 9. The use of swarm signal processing for early detection of emergencies. 10. Swarm based collaborative cyber security infrastructure