Scalability of Confidence-Based Autonomy Multi-Robot Demonstration Learning
نویسندگان
چکیده
In this paper, we present the first application of demonstration learning to more than two robots and perform an analysis of the scalability of the Confidence-Based Autonomy (CBA) multi-robot demonstration learning algorithm. Through experimental evaluation using up to seven Sony AIBO robots, we examine how the number of robots being taught by a human teacher at the same time affects the number of demonstrations required to learn the task, the time and attention demands on the teacher, and the delay each robot experiences in obtaining a demonstration. Additionally, we contribute an analysis of a special case of CBA learning in which all robots learn a common task policy.
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