# Learning and tuning fuzzy logic controllers through reinforcements

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### Cites background from "Learning and tuning fuzzy logic con..."

...Parameters of a FLS can also be trained on-line using reinforcement learning [ 4 ]....

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### Additional excerpts

...works, whose connection weights correspond to the parameters of fuzzy reasoning [38], [123], [124], [135], [187], [220], [231], [232], [264]....

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### Cites methods from "Learning and tuning fuzzy logic con..."

...Only the center of each Gaussian membership function is delivered to the next layer for the local mean of maximum (LMOM) defuzzification operation [23] and the width is used for output clustering only....

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##### References

17,604 citations

### "Learning and tuning fuzzy logic con..." refers background or methods in this paper

...This structure is shown in Fig. 4. The learning algorithm is composed of Sutton’s AHC algorithm [26] for the output unit and the error back-propagation algorithm [ 24 ] for the hidden units....

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...The weight update function for the hidden layer is based on a modified version of the error back-propagation algorithm [ 24 ]....

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...[ 24 ] or some sort of line-search technique to determine the optimal step size at each point 1151....

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### "Learning and tuning fuzzy logic con..." refers methods in this paper

...The center and spreads may be considered as weights on the input links, analogous to the approach taken with radial-basis-function units in neural networks [ 20 ]....

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