Reduction of the gap between simulated and real environments in evolutionary robotics: a dynamically-rearranging neural network approach

Akio Ishiguro, Seiji Tokura, Toshiyuki Kondo, Yoshiki Uchikawa, Peter Eggenberger

研究成果: Conference article査読

13 被引用数 (Scopus)

抄録

Recently, the Evolutionary Robotics approach has been attracting a lot of concern in robotics and artificial life communities. In this approach, neural networks are widely used to construct controllers for autonomous mobile agents, since they intrinsically have nonlinear mapping, generalization, noise-tolerant abilities and so on. However, the followings are still open questions: 1) the gap between simulated and real environments, 2) the evolutionary and learning phase are completely separated, and 3) the conflict between stability and evolvability/adaptability. In this paper, we particularly focus on the gap problem, and try to alleviate this by incorporating the concept of dynamic rearrangement function of biological neural networks with the use of neuromodulators. Simulation and real experimental results show that the proposed approach is highly promising.

本文言語English
ページ(範囲)III-239 - III-244
ジャーナルProceedings of the IEEE International Conference on Systems, Man and Cybernetics
3
出版ステータスPublished - 1999
外部発表はい
イベント1999 IEEE International Conference on Systems, Man, and Cybernetics 'Human Communication and Cybernetics' - Tokyo, Jpn
継続期間: 1999 10月 121999 10月 15

ASJC Scopus subject areas

  • 制御およびシステム工学
  • ハードウェアとアーキテクチャ

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