Download Achieving Consensus in Robot Swarms: Design and Analysis of by Gabriele Valentini PDF

By Gabriele Valentini

This e-book specializes in the layout and research of collective decision-making recommendations for the best-of-n challenge. After offering a formalization of the constitution of the best-of-n challenge supported by means of a entire survey of the swarm robotics literature, it introduces the functioning of a collective decision-making method and identifies a suite of mechanisms which are crucial for a method to unravel the best-of-n challenge. The best-of-n challenge is an abstraction that captures the common requirement of a robotic swarm to decide on one alternative from of a finite set while optimizing benefits and prices. The booklet leverages the identification of those mechanisms to increase a modular and model-driven technique to layout collective decision-making ideas and to investigate their functionality at assorted point of abstractions. finally, the writer presents a sequence of case reports within which the proposed technique is used to layout diverse recommendations, utilizing robotic experiments to teach how the designed thoughts may 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

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De Oliveira, F. Mondada, Decentralized self-selection of swarm trajectories: from dynamical systems theory to robotic implementation. Swarm Intell. 8(4), 329– 351 (2014) A. Scheidler, Dynamics of majority rule with differential latencies. Phys. Rev. E 83, 031116 (2011) A. Scheidler, A. Brutschy, E. Ferrante, M. Dorigo, The k-unanimity rule for self-organized decisionmaking in swarms of robots. IEEE Trans. Cybern. 46(5), 1175–1188 (2016) I. Schizas, G. Giannakis, S. Roumeliotis, A. Ribeiro, Consensus in ad hoc WSNs with noisy links Part II: distributed estimation and smoothing of random signals.

7426, LNCS (Springer, 2012), pp. 381–390 G. Francesca, M. Brambilla, A. Brutschy, V. Trianni, M. Birattari, AutoMoDe: a novel approach to the automatic design of control software for robot swarms. Swarm Intell. R. C. B. F. T. Sumpter, Information flow, opinion polling and collective intelligence in house-hunting social insects. Philos. Trans. R. Soc. B: Biol. Sci. R. O. Richardson, N. W. D. M. R. Marshall, T. Schlegel, Speed-cohesion trade-offs in collective decision making in ants and the concept of precision in animal behaviour.

Moreover, these studies are distributed in five separate lines of research for each category. Differently, the swarm robotics literature has considered a significantly smaller number of studies that focused on the best-of-n problem in the case in which the option quality is determined by an internal preference factor. The majority of these studies considered application scenarios where the option quality is either independent of environmental bias factors or it is positively influenced by them.

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