Method of Constructing Autonomous Decentralized Systems Using Classifier Systems : Application to Gait Acquisition of 6-Legged Robot

It is difficult to control large complex systems by centralized control. Therefore, autonomous decentralized systems which have variety, flexibility and fault tolerability, have been studied recently. In this paper, we propose an autonomous decentralized system comprised of classifier systems. Class...

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Bibliographic Details
Published inTransactions of the Japan Society of Mechanical Engineers Series C Vol. 60; no. 580; pp. 4245 - 4251
Main Authors Yamada, Yasuharu, Ishiguro, Akio, Uchikawa, Yoshiki
Format Journal Article
LanguageJapanese
Published The Japan Society of Mechanical Engineers 25.12.1994
Subjects
6-Legged Robot
Autonomous Decentralized System
Biomechanics
Classifier System
Gait Acquisition
Genetic Algorithm
Learning
Moving Robot
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Summary:It is difficult to control large complex systems by centralized control. Therefore, autonomous decentralized systems which have variety, flexibility and fault tolerability, have been studied recently. In this paper, we propose an autonomous decentralized system comprised of classifier systems. Classifier systems are parallel, message-passing, rule-based systems that learn through credit assignment and rule discovery (the genetic algorithm). In our method, each subsystem is controlled by an individual classifier system, and it generates production rules autonomously by exchanging information with adjacent subsystems. We test the system on a 6-legged robot, in computer simulations, which learns how to coordinate its legs so as to walk forward, as a practical example.
ISSN:0387-5024
1884-8354
DOI:10.1299/kikaic.60.4245