Achieving Consensus in Robot Swarms - Design and Analysis of Strategies for the best-of-n Problem (Hardcover, 1st ed. 2017)

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, using robot experiments to show how the designed strategies can be ported to different application scenarios.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Studies in Computational Intelligence, 706
Release date:	February 2017
First published:	2017
Authors:	Gabriele Valentini
Dimensions:	235 x 155 x 11mm (L x W x T)
Format:	Hardcover
Pages:	146
Edition:	1st ed. 2017
ISBN-13:	978-3-319-53608-8
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics Promotions
LSN:	3-319-53608-7
Barcode:	9783319536088

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