Advertisement

© 2018

Swarms and Network Intelligence in Search

Benefits

  • Presents recent research on swarms and network intelligence in search?systems

  • Applies swarm intelligence methods to search technology

  • Written by experts in the field

Book

Part of the Studies in Computational Intelligence book series (SCI, volume 729)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein
    Pages 1-14
  3. Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein
    Pages 15-49
  4. Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein
    Pages 51-89
  5. Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein
    Pages 91-127
  6. Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein
    Pages 129-153
  7. Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein
    Pages 155-185
  8. Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein
    Pages 187-205
  9. Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein
    Pages 207-238

About this book

Introduction

This book offers a comprehensive analysis of the theory and tools needed for the development of an efficient and robust infrastructure for the design of collaborative patrolling unmanned aerial vehicle (UAV) swarms, focusing on its applications for tactical intelligence drones. It discusses frameworks for robustly and near-optimally analyzing flocks of semi-autonomous vehicles designed to efficiently perform the ongoing dynamic patrolling and scanning of pre-defined “search regions”. It discusses the theoretical limitations of such systems, as well as the trade-offs between the systems’ various economic and operational parameters.

Current UAV systems rely mainly on human operators for the design and adaptation of drones’ flying routes. However, recent technological advances have introduced new systems, comprised of a small number of self-organizing vehicles, manually guided at the swarm level by a human operator.

With the growing complexity of such
man-supervised architectures, it is becoming increasingly harder to guarantee a pre-defined level of performance. The use of large scale swarms of UAVs as a combat and reconnaissance platform therefore necessitates the development of an efficient optimization mechanism of their utilization, specifically in the design and maintenance of their patrolling routes.

The book is intended for researchers and engineers in the fields of swarms systems and autonomous drones. 

Keywords

Computational Intelligence Network Intelligence Swarm Intelligence Computational Complexity Collaborative Patrolling Autonomous Decentralized Systems

Authors and affiliations

  1. 1.MIT Media LabMassachusetts Institute of TechnologyCambridgeUSA
  2. 2.MIT Media LabMassachusetts Institute of TechnologyCambridgeUSA
  3. 3.Computer Science DepartmentIsraeli Institute of Technology (Technion)HaifaIsrael

Bibliographic information

  • Book Title Swarms and Network Intelligence in Search
  • Authors Yaniv Altshuler
    Alex Pentland
    Alfred M. Bruckstein
  • Series Title Studies in Computational Intelligence
  • Series Abbreviated Title Studies Comp.Intelligence
  • DOI https://doi.org/10.1007/978-3-319-63604-7
  • Copyright Information Springer International Publishing AG 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Hardcover ISBN 978-3-319-63602-3
  • Softcover ISBN 978-3-319-87591-0
  • eBook ISBN 978-3-319-63604-7
  • Series ISSN 1860-949X
  • Series E-ISSN 1860-9503
  • Edition Number 1
  • Number of Pages IX, 238
  • Number of Illustrations 63 b/w illustrations, 53 illustrations in colour
  • Topics Computational Intelligence
    Artificial Intelligence
  • Buy this book on publisher's site
Industry Sectors
Automotive
Chemical Manufacturing
Biotechnology
IT & Software
Telecommunications
Law
Consumer Packaged Goods
Pharma
Materials & Steel
Finance, Business & Banking
Electronics
Energy, Utilities & Environment
Aerospace
Oil, Gas & Geosciences
Engineering

Reviews

“The book is a solid attempt to formally characterize the properties of domains and the swarms of robots operating in them. The algorithms are often described with figures that show sample environments and how the operations progress over time. This provides a good understanding of how the algorithms work.” (M. Gini, Computing Reviews, January, 2019)​