Achieving Consensus in Robot Swarms: Design and Analysis of Strategies for the best-of-n Problem: 706 (Studies in Computational Intelligence, 706) - Image 1

£86.97

Springer Achieving Consensus in Robot Swarms: Design and Analysis of Strategies for the best-of-n Problem: 706 (Studies in Computational Intelligence, 706)

Name: Achieving Consensus in Robot Swarms: Design and Analysis of Strategies for the best-of-n Problem: 706 (Studies in Computational Intelligence, 706)
Brand: Springer
Price: 86.97 GBP
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AI & Machine Learning

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Description

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. From the Back Cover 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.

Product Specifications

Brand: Springer
Format: paperback
ASIN: 3319851969
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 04 May 2018
Listed Since: 08 May 2018

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Springer Achieving Consensus in Robot Swarms: Design and Analysis of Strategies for the best-of-n Problem: 706 (Studies in Computational Intelligence, 706)

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