Overview
- Covers collective decision-making strategies for robot swarms
- Focuses on the design of self-organized solutions to the best-of-n problem—the problem of deciding which alternative among a finite set of options is the most beneficial choice for the swarm
- Deals with both theoretical and experimental aspects of collective decision-making and includes the results of experiments performed with a swarm of 100 robots
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 706)
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About this book
This book focuses on the design and analysis of collective decision-making strategies for the best-of-n problem. After providing a formalization of the structure of the best-of-n problem supported by a comprehensive survey of the swarm robotics literature, it introduces the functioning of a collective decision-making strategy and identifies a set of mechanisms that are essential for a strategy to solve the best-of-n problem. The best-of-n problem is an abstraction that captures the frequent requirement of a robot swarm to choose one option from of a finite set when optimizing benefits and costs. The book leverages the identification of these mechanisms to develop a modular and model-driven methodology to design collective decision-making strategies and to analyze their performance at different level of abstractions. Lastly, the author provides a series of case studies in which the proposed methodology is used to design different strategies, usingrobot experiments to show how the designed strategies can be ported to different application scenarios.
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Keywords
Table of contents (9 chapters)
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Background and Methodology
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Mathematical Modeling and Analysis
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Robot Experiments
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Discussion and Annexes
Authors and Affiliations
Bibliographic Information
Book Title: Achieving Consensus in Robot Swarms
Book Subtitle: Design and Analysis of Strategies for the best-of-n Problem
Authors: Gabriele Valentini
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-319-53609-5
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-53608-8Published: 22 February 2017
Softcover ISBN: 978-3-319-85196-9Published: 04 May 2018
eBook ISBN: 978-3-319-53609-5Published: 14 February 2017
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XIV, 146
Number of Illustrations: 9 b/w illustrations, 37 illustrations in colour
Topics: Computational Intelligence, Robotics and Automation, Artificial Intelligence
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