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Volume 41 Issue 1
Jan.  2015
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Journal of Beijing University of Aeronautics and Astronautics  > 2015  >  41(1): 96-101.
ZHOU Yanan, GONG Guanghong. Intelligent decision-making algorithm based on bounded FART-Q[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(1): 96-101. doi: 10.13700/j.bh.1001-5965.2014.0076(in Chinese)
Citation: ZHOU Yanan, GONG Guanghong. Intelligent decision-making algorithm based on bounded FART-Q[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(1): 96-101. doi: 10.13700/j.bh.1001-5965.2014.0076(in Chinese)
shu

Intelligent decision-making algorithm based on bounded FART-Q

doi: 10.13700/j.bh.1001-5965.2014.0076

  • School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

  • Received Date: 27 Feb 2014
  • Publish Date: 20 Jan 2015
    Abstract
  • Fuzzy adaptive resonance theory (ART) with bounded side length was proposed to address the problem emerged while applying fuzzy ART to intelligent decision-making. Integrating the modified fuzzy ART and Q learning algorithm, bounded fuzzy ART-Q learning (FART-Q) intelligent decision-making network was built. The original fuzzy ART might make unreasonable classifications only according to the fuzzy similarity between input vector and weight vector, without considering the physical meaning of the state variables. To solve this problem, a modified algorithm was proposed, strengthening the resonance condition of fuzzy ART with bounded side length. The improvement made it possible both to limit the side length according to the physical meaning of the state variables and to reduce the number of categories. The minefield navigation simulation was conducted to verify the availability and effectiveness of bounded FART-Q. Compared with the original fuzzy ART, the modified algorithm is able to make classifications more reasonably with higher success rate and less operation time.

     

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