Multi-robot system learning based on evolutionary classification
Moscow State University of Information Technologies, Radio Engineering and Electronics (MIREA), Russia
a Corresponding author: firstname.lastname@example.org
This paper presents a novel machine learning method for agents of a multi-robot system. The learning process is based on knowledge discovery through continual analysis of robot sensory information. We demonstrate that classification trees and evolutionary forests may be a basis for creation of autonomous robots capable both of learning and knowledge exchange with other agents in multi-robot system. The results of experimental studies confirm the effectiveness of the proposed approach.
© Owned by the authors, published by EDP Sciences, 2016
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