Toward seamless transfer from simulated to real worlds: A dynamically-rearranging neural network approach

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

研究成果: Conference contribution

9 被引用数 (Scopus)

抄録

In the field of evolutionary robotics artificial neural networks are often used to construct controllers for autonomous agents, because they have useful properties such as the ability to generalize or to be noise-tolerant. Since the process to evolve such controllers in the real- world is very time-consuming, one usually uses simulators to speed up the evolutionary process. By doing so a new problem arises: The controllers evolved in the simulator show not the same fitness as those in the real-world. A gap between the simulated and real environments exists. In order to alleviate this problem we introduce the concept of neuromodulators, which allows to evolve neural networks which can adjust not only the synaptic weights, but also the structure of the neural network by blocking and/or activating synapses or neurons. We apply this concept to a peg-pushing problem for Khepera™ and compare our method to a conventional one, which evolves directly the synaptic weights. Simulation and real experimental results show that the proposed approach is highly promising.

本文言語English
ホスト出版物のタイトルAdvances in Robot Learning - 8th European Workshop on Learning Robots, EWLR-8, Proceedings
編集者Jeremy Wyatt, John Demiris
出版社Springer Verlag
ページ44-60
ページ数17
ISBN(印刷版)3540411623, 9783540411628
DOI
出版ステータスPublished - 2000
外部発表はい
イベント8th European Workshop on Learning Robots, EWLR 1999 - Lausanne, Switzerland
継続期間: 1999 9 181999 9 18

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
1812
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other8th European Workshop on Learning Robots, EWLR 1999
CountrySwitzerland
CityLausanne
Period99/9/1899/9/18

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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