By Gabriele Valentini
This publication makes a speciality of the layout and research of collective decision-making thoughts for the best-of-n problem. After supplying a formalization of the constitution of the best-of-n problem supported by means of a accomplished survey of the swarm robotics literature, it introduces the functioning of a collective decision-making process 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 common requirement of a robotic swarm to settle on one choice from of a ﬁnite set whilst optimizing beneﬁts and prices. The booklet leverages the identiﬁcation of those mechanisms to advance a modular and model-driven method to layout collective decision-making suggestions and to research their functionality at diversified point of abstractions. finally, the writer presents a sequence of case stories during which the proposed method is used to layout diverse thoughts, utilizing robotic experiments to teach how the designed thoughts should be ported to diverse program scenarios.
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Achieving Consensus in Robot Swarms: Design and Analysis of Strategies for the best-of-n Problem (Studies in Computational Intelligence) by Gabriele Valentini