JRM Vol.20 No.5 pp. 757-774
doi: 10.20965/jrm.2008.p0757


Reinforcement Signal Propagation Algorithm for Logic Circuit

Chyon Hae Kim*, Tetsuya Ogata**, and Shigeki Sugano*

*Department of Mechanical Engineering, Waseda University, 3-4-1, Okubo, Shinjuku-ku, Tokyo 169-8555, Japan

**Graduate School of Informatics, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan

February 16, 2008
August 19, 2008
October 20, 2008
topology, self-organization, neural network, reinforcement learning, robot
This paper proposes a group of network elements, SONE, that self-organizes network topology, aiming at online and real-time learning and adaptation in robots. SONE, consisting of node elements and link elements, develops network topology by repeating generation and elimination of themselves based on reinforcement signals that are propagated and stored between the elements. This technique proved successful in simulations in which a mobile robot avoided obstacles, and it convinced us of its feasibility for online learning.
Cite this article as:
C. Kim, T. Ogata, and S. Sugano, “Reinforcement Signal Propagation Algorithm for Logic Circuit,” J. Robot. Mechatron., Vol.20 No.5, pp. 757-774, 2008.
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