Applied Swarm Intelligence

Inbunden, Engelska, 2024

AvYaniv Altshuler,MA) Altshuler, Yaniv (Research Affiliate, MIT Media Lab

2 469 kr

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This book provides a comprehensive analysis of the tools and techniques used today for designing 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, bioinformatics, and military applications. Theoretical and practical limitations of such systems, as well as trade-offs between the various economic and operational parameters of the systems, are discussed. The book is intended for researchers and engineers in the fields of swarm systems, economics, agriculture, nutrition, and operation research.

Produktinformation

Utgivningsdatum2024-12-19
Mått156 x 234 x 23 mm
Vikt790 g
FormatInbunden
SpråkEngelska
Antal sidor332
FörlagTaylor & Francis Ltd
ISBN9780367226879

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Yaniv Altshuler, a leading expert in Artificial Intelligence, is a researcher at the MIT Media Lab, Cambridge, Massachusetts, USA and a dynamic entrepreneur. Over the past decade he has used his expertise to advise leading financial institutes and government agencies worldwide. Yaniv is the author of 3 books on the topic of AI and has published over 80 scientific papers and filed 18 patents. His research has been covered by Harvard Business Review, Financial Times, Communications of the ACM, IEEE Spectrum and others.

Preface. Recent Developments in the Theory and Applicability of Swarm Search. Modeling and Prediction of Ride Sharing Utilization Dynamics. The Dynamics of Autonomous Drone Swarms in Surveillance: Exploring Efficiency, Feasibility, and Complexity. Defending Large-Scale Critical Infrastructures using a Swarm of Drones. Socioeconomic Patterns of Twitter Activity. From Microbes to Methane: AI-Based Predictive Modeling of Feed Additive Efficacy in Dairy Cows.