Fuzzy control rules extraction from perception-based information using computing with words
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Intelligent information systems and applications
Information Integration for Robot Learning Using Neural Fuzzy Systems
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Bio-inspired Applications of Connectionism-Part II
Dynamic balance of a biped robot using fuzzy reinforcement learning agents
Fuzzy Sets and Systems - Special issue: Fuzzy set techniques for intelligent robotic systems
An evolutionary approach to fuzzy rule-based model synthesis using indices for rules
Fuzzy Sets and Systems - Theme: Modeling and control
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IEEE Transactions on Knowledge and Data Engineering
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Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence
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This paper proposes an approach where the interpretation of manual control strategies is carried out by modeling the human operator as a fuzzy logic controller. The linguistic rules thus obtained can provide a better insight into the operator's actions, allowing mistakes to be more easily pinpointed and corrected. Instead of extracting the control rules directly from raw experimental data, an intermediary ARMA model for the operator is employed to improve the data consistency. For illustration, this method is applied to the problem of supervising an apprentice operator, with basis on rules extracted from the actions of an experienced manual operator