Efficient organization of network topology based on reinforcement signals

Chyon Hae Kim; Shigeki Sugano; Tetsuya Ogata

doi:10.1109/IROS.2006.282338

Efficient organization of network topology based on reinforcement signals

Chyon Hae Kim^*, Shigeki Sugano, Tetsuya Ogata

^*Corresponding author for this work

School of Creative Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

We developed a learning system for autonomous robots that allows for autonomous exploration of the effective output, and has simple external parameters and a low calculation cost. We propose the concept of self-organizing network elements (SONE) for creating learning systems with these characteristics. We created and evaluated a self-organizing logic circuit by using this concept. Our results indicated this learning system had the characteristics.

Original language	English
Title of host publication	2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006
Pages	3154-3159
Number of pages	6
DOIs	https://doi.org/10.1109/IROS.2006.282338
Publication status	Published - 2006
Event	2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006 - Beijing, China Duration: 2006 Oct 9 → 2006 Oct 15

Publication series

Name	IEEE International Conference on Intelligent Robots and Systems

Conference

Conference	2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006
Country/Territory	China
City	Beijing
Period	06/10/9 → 06/10/15

ASJC Scopus subject areas

Control and Systems Engineering
Software
Computer Vision and Pattern Recognition
Computer Science Applications

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10.1109/IROS.2006.282338

Cite this

Efficient organization of network topology based on reinforcement signals. / Kim, Chyon Hae; Sugano, Shigeki ; Ogata, Tetsuya.

2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006. 2006. p. 3154-3159 4058881 (IEEE International Conference on Intelligent Robots and Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kim, CH, Sugano, S & Ogata, T 2006, Efficient organization of network topology based on reinforcement signals. in 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006., 4058881, IEEE International Conference on Intelligent Robots and Systems, pp. 3154-3159, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006, Beijing, China, 06/10/9. https://doi.org/10.1109/IROS.2006.282338

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title = "Efficient organization of network topology based on reinforcement signals",

abstract = "We developed a learning system for autonomous robots that allows for autonomous exploration of the effective output, and has simple external parameters and a low calculation cost. We propose the concept of self-organizing network elements (SONE) for creating learning systems with these characteristics. We created and evaluated a self-organizing logic circuit by using this concept. Our results indicated this learning system had the characteristics.",

author = "Kim, {Chyon Hae} and Shigeki Sugano and Tetsuya Ogata",

year = "2006",

doi = "10.1109/IROS.2006.282338",

language = "English",

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series = "IEEE International Conference on Intelligent Robots and Systems",

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note = "2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006 ; Conference date: 09-10-2006 Through 15-10-2006",

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AU - Sugano, Shigeki

AU - Ogata, Tetsuya

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AB - We developed a learning system for autonomous robots that allows for autonomous exploration of the effective output, and has simple external parameters and a low calculation cost. We propose the concept of self-organizing network elements (SONE) for creating learning systems with these characteristics. We created and evaluated a self-organizing logic circuit by using this concept. Our results indicated this learning system had the characteristics.

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Y2 - 9 October 2006 through 15 October 2006

ER -

Efficient organization of network topology based on reinforcement signals

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