Abstract—The Bias and Raising Threshold (BRT) algorithm is one of the methods for the best-of-n problem (BSTn) that allows a group of robots to find out the appropriate collective option among a set of n alternatives. This paper improves the BRT algorithm by using multiple voting for shortening the search time. Concretely, each robot is considered that might be able to vote multiple times in a selection. The experimental results revealed that the search time was only dramatically reduced but also the search accuracy was improved, especially in difficult problems where there are a large number of options (n≥2).
Index Terms—BRT algorithm, multiple voting, the best-of-n problem, complex systems, collective intelligence, group decision-making.
N. H. Phung, M. Kubo, and H. Sato are with the Computer Science, National Defense Academy of Japan, Hashirimizu 1-10-20, Yokosuka, Kanagawa, Japan (e-mail: ed17006@nda.ac.jp, masaok@nda.ac.jp, hsato@nda.ac.jp).
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Cite:N. H. Phung, M. Kubo, and H. Sato, "Efficient Searching by Bias and Raising Threshold Algorithm Using Multiple Voting in the Best-of-n Problem," International Journal of Computer Theory and Engineering vol. 11, no. 3, pp. 39-45, 2019.
