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Adaptation of Fuzzy Cognitive Maps – a Comparison Study

Author(s): Ján Vaščák | Ladislav Madarász

Journal: Acta Polytechnica Hungarica
ISSN 1785-8860

Volume: 7;
Issue: 3;
Start page: 109;
Date: 2010;
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Keywords: adaptation methods | fuzzy cognitive learning | Hebbian learning | supervised learning

This paper deals with the experimental study and comparison of variousadaptation methods for setting-up parameters of fuzzy cognitive maps (FCMs). A survey isgiven of the best known methods, which are mostly based on unsupervised learning. Theauthors show better performance using supervised learning, namely least mean squareapproaches. Experiments were done on a simulation example of autonomous vehiclenavigation. The paper is concluded by comparing their efficacy and properties.
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