The best-of-n problem in robot swarms: formalization, state of the art, and novel perspectives
Research output: Contribution to journal › Article › peer-review
Colleges, School and Institutes
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.
|Number of pages||18|
|Journal||Frontiers in Robotics and Artificial Intelligence|
|Publication status||Published - 13 Mar 2017|
- best-of-n problem, collective decision-making, consensus achievement, swarm robotics, self-organization