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Action learning of a mobile robot based on perceiving-acting cycle

Naoyuki Kubota, Hiroyuki Masuta

Year
2004
Citations
4

Abstract

This paper proposes a learning method of a mobile robot with structured intelligence in a changing environment. Modular neural networks are applied for action control based on perceiving-acting cycle of ecological psychology. The robot extracts action rules from the behavior knowledge described by fuzzy rules. Next, we conduct several experiments using a mobile robot. The experimental results show the robot can learn actions based on the perceiving-acting cycle.

Keywords

Mobile robotComputer scienceAction (physics)RobotArtificial intelligenceRobot learningModular designFuzzy logicSocial robotHuman–computer interaction

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