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

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

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
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

出版系列

名字IEEE International Conference on Fuzzy Systems
ISSN(列印)1098-7584

其他

其他2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008
國家/地區中国
城市Hong Kong
期間2008/06/012008/06/06

ASJC Scopus subject areas

  • 軟體
  • 理論電腦科學
  • 人工智慧
  • 應用數學

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