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Teacher's load and timing of teaching based on interactive evolutionary robotics

Daisuke Katagami, Seiji Yamada

Year
2004
Citations
2

Abstract

We have proposed a fast learning method that enables a mobile robot to acquires autonomous behaviors from interaction between human and robot. In this research we develop a behavior learning method ICS (interactive classifier system) using interactive evolutionary computation considering an operator's teaching cost. As a result, a mobile robot is able to quickly learn rules by directly teaching from an operator. ICS is a novel evolutionary robotics approach using classifier system. In this paper, we investigate teacher's physical and mental load and proposed a teaching method based on timing of instruction using ICS.

Keywords

Evolutionary roboticsArtificial intelligenceRoboticsComputer scienceMobile robotRobotClassifier (UML)Evolutionary computationComputationRobot learning

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