Efficient collective search by BRT algorithm using fast rising threshold agent
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https://doi.org/10.54939/1859-1043.j.mst.CSCE5.2021.102-108Keywords:
Best-of-n problem, BRT algorithm, Swarm robotics, Collective decision-making.Abstract
The BRT algorithm is a method for the best-of-n problem that allows a group of distributed robots to find out the most appropriate collective option among many alternatives. Computer experiments show that the time required for finding out the best option is proportional to the number of options. In this paper, we aim to shorten this search time by introducing a few agents whose threshold increases faster than the normal one to achieve higher scalability of the BRT algorithm. The results show that the search time is reduced, and the variance is improved, especially under challenging problems where robots are required to make decisions out of a large number of options.
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