AUTHOR=Valentini Gabriele , Ferrante Eliseo , Dorigo Marco TITLE=The Best-of-n Problem in Robot Swarms: Formalization, State of the Art, and Novel Perspectives JOURNAL=Frontiers in Robotics and AI VOLUME=4 YEAR=2017 URL=https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2017.00009 DOI=10.3389/frobt.2017.00009 ISSN=2296-9144 ABSTRACT=

The ability to collectively choose the best among a finite set of alternatives is a fundamental cognitive skill for robot swarms. In this paper, we propose a formal definition of the best-of-n problem and a taxonomy that details its possible variants. Based on this taxonomy, we analyze the swarm robotics literature focusing on the decision-making problem dealt with by the swarm. We find that, so far, the literature has primarily focused on certain variants of the best-of-n problem, while other variants have been the subject of only a few isolated studies. Additionally, we consider a second taxonomy about the design methodologies used to develop collective decision-making strategies. Based on this second taxonomy, we provide an in-depth survey of the literature that details the strategies proposed so far and discusses the advantages and disadvantages of current design methodologies.