By Gabriele Valentini
This publication makes a speciality of the layout and research of collective decision-making suggestions for the best-of-n problem. After supplying a formalization of the constitution of the best-of-n problem supported via a accomplished survey of the swarm robotics literature, it introduces the functioning of a collective decision-making approach and identiﬁes a suite of mechanisms which are crucial for a method to unravel the best-of-n problem. The best-of-n problem is an abstraction that captures the widespread requirement of a robotic swarm to settle on one choice from of a ﬁnite set whilst optimizing beneﬁts and prices. The ebook leverages the identiﬁcation of those mechanisms to advance a modular and model-driven technique to layout collective decision-making innovations and to investigate their functionality at varied point of abstractions. finally, the writer presents a sequence of case experiences within which the proposed method is used to layout assorted recommendations, utilizing robotic experiments to teach how the designed thoughts should be ported to varied software scenarios.
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Extra info for Achieving Consensus in Robot Swarms: Design and Analysis of Strategies for the best-of-n Problem (Studies in Computational Intelligence)
Achieving Consensus in Robot Swarms: Design and Analysis of Strategies for the best-of-n Problem (Studies in Computational Intelligence) by Gabriele Valentini