By Gabriele Valentini
This e-book specializes in the layout and research of collective decision-making suggestions for the best-of-n challenge. After offering a formalization of the constitution of the best-of-n challenge supported by way of a accomplished survey of the swarm robotics literature, it introduces the functioning of a collective decision-making technique and identiﬁes a suite of mechanisms which are crucial for a technique to resolve the best-of-n challenge. The best-of-n challenge is an abstraction that captures the common requirement of a robotic swarm to settle on one alternative from of a ﬁnite set while optimizing beneﬁts and prices. The publication leverages the identiﬁcation of those mechanisms to advance a modular and model-driven method to layout collective decision-making techniques and to research their functionality at diversified point of abstractions. finally, the writer offers a chain of case reviews during which the proposed technique is used to layout diversified thoughts, utilizing robotic experiments to teach how the designed innovations could be ported to varied program scenarios.
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Publication Date: 2012-12-01
Number of Pages: 224
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Additional info for Achieving Consensus in Robot Swarms: Design and Analysis of Strategies for the best-of-n Problem
Auton. Agents Multi-Agent Syst. D. K. Visscher, T. M. R. R. Marshall, Stop signals provide cross inhibition in collective decision-making by honeybee swarms. Science 335(6064), 108–111 (2012) O. Soysal, E. Sahin, ¸ A macroscopic model for self-organized aggregation in swarm robotic systems, ed. By E. M. T. Winfield. Swarm Robotics, vol. 4433. LNCS (Springer, 2007), pp. M. F. C. Hamann, R. Heil, Distributed, physics-based control of swarms of vehicles. Auton. T. Sumpter, Collective Animal Behavior (Princeton University Press, Princeton, 2010) B.
R. E. R. Marshall, A mechanism for value-sensitive decision-making. C. Parker, H. Zhang, Cooperative decision-making in decentralized multiple-robot systems: the best-of-n problem. IEEE/ASME Trans. Mechatron. C. Parker, H. Zhang, Collective unary decision-making by decentralized multiple-robot systems applied to the task-sequencing problem. Swarm Intell. C. Parker, H. Zhang, Biologically inspired collective comparisons by robotic swarms. Int. J. Robot. Res. 30(5), 524–535 (2011) D. Payton, M. Daily, R.
R. Marshall, A mechanism for value-sensitive decision-making. C. Parker, H. Zhang, Cooperative decision-making in decentralized multiple-robot systems: the best-of-n problem. IEEE/ASME Trans. Mechatron. C. Parker, H. Zhang, Collective unary decision-making by decentralized multiple-robot systems applied to the task-sequencing problem. Swarm Intell. C. Parker, H. Zhang, Biologically inspired collective comparisons by robotic swarms. Int. J. Robot. Res. 30(5), 524–535 (2011) D. Payton, M. Daily, R.