Brain-Inspired Information Technology pp 171-175

Part of the Studies in Computational Intelligence book series (SCI, volume 266) | Cite as

Effective and Adaptive Learning Based on Diversive/Specific Curiosity

  • Naoki Shimo
  • Shaoning Pang
  • Keiichi Horio
  • Nikola Kasabov
  • Hakaru Tamukoh
  • Takanori Koga
  • Satoshi Sonoh
  • Hirohisa Isogai
  • Takeshi Yamakawa

Abstract

In this paper, an effective and adaptive learning model, in which a concept of curiosity is used, is proposed. The key idea of the proposed method is to introduce the diversive curiosity in addition to specific curiosity. Furthermore we employ the concept of threshold, which control timing of switching two curiosity modes. By employing two curiosity and making a proper selection of them, a learning ability and adaptability is improved. The effectiveness of the proposed method is verified by some simulations.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Naoki Shimo
    • 1
  • Shaoning Pang
    • 2
  • Keiichi Horio
    • 1
  • Nikola Kasabov
    • 2
  • Hakaru Tamukoh
    • 1
  • Takanori Koga
    • 1
  • Satoshi Sonoh
    • 1
  • Hirohisa Isogai
    • 1
  • Takeshi Yamakawa
    • 1
  1. 1.Department of Brain Science and Engineering, Graduate School of Life Science and Systems EngineeringKyushu Institute of TechnologyKitakyushuJapan
  2. 2.Knowledge Engineering and Discovery Research InstituteAuckland University of TechnologyAucklandNew Zealand

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