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General Information
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2019 Vol.11(3): 39-45 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2019.V11.1239

Efficient Searching by Bias and Raising Threshold Algorithm Using Multiple Voting in the Best-of-n Problem

N. H. Phung, M. Kubo, and H. Sato
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).


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.

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