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- W2018688614 abstract "The fuzzy inference system (FIS) is an expert system based on if-then rules which are extracted from experts' knowledge. To obtain experts' knowledge, however, is not always easy and may be expensive. Q-learning is one type of reinforcement learning in which the desired sequence of actions can be obtained by trial and error without a priori knowledge about the model. In this paper, the extended rule and the interpolation technique are proposed to combine FIS and Q-learning. The resulting self-organizing fuzzy inference system by Q-learning (SOFIS-Q) has the capability of generating the fuzzy rule base automatically and on-line by trial and error without any experts' knowledge." @default.
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- W2018688614 date "1999-01-01" @default.
- W2018688614 modified "2023-09-28" @default.
- W2018688614 title "Self-organizing fuzzy inference system by Q-learning" @default.
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- W2018688614 doi "https://doi.org/10.1109/fuzzy.1999.793268" @default.
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