Adaptive learning approach of integrating evolution fuzzy-neural networks and Q-learning for mobile robots

Hong Jian Zhon, Wei Min Hsieh, Yih-Guang Leu, Chin-Ming Hong

研究成果: 書貢獻/報告類型會議貢獻

摘要

In the paper, an adaptive learning approach of integrating evolution fuzzy-neural networks and Q-learning is developed so that a mobile robot can adapt itself to a real and complex environment. Specifically, based on Q-value and an evolution method that adjusts their parameter values of the fuzzy-neural networks, the mobile robot evolves better strategies to adapt to the environment. However, in most studies of evolution learning, the learning of mobile robots often requires a simulator and an enormous amount of evolution time so as to perform a task. Therefore, we are to integrate Q-learning into the evolution fuzzy-neural networks to avoid the requirement of the simulator. Experiment results of a mobile robot illustrate the performance of the proposed approach.

原文英語
主出版物標題2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008
頁面1902-1906
頁數5
DOIs
出版狀態已發佈 - 2008 十一月 7
事件2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008 - Hong Kong, 中国
持續時間: 2008 六月 12008 六月 6

其他

其他2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008
國家中国
城市Hong Kong
期間08/6/108/6/6

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Artificial Intelligence
  • Applied Mathematics

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  • 引用此

    Zhon, H. J., Hsieh, W. M., Leu, Y-G., & Hong, C-M. (2008). Adaptive learning approach of integrating evolution fuzzy-neural networks and Q-learning for mobile robots. 於 2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008 (頁 1902-1906). [4630629] https://doi.org/10.1109/FUZZY.2008.4630629