GAITS: Fuzzy sets-based algorithms for computing strategies using genetic algorithms
This paper introduces a new method combining Fuzzy Logic and Genetic Algorithms to allow Intelligent Tutoring Systems to be efficient. We consider supervised teaching where the teacher assigns a initial profile and a finale profile to each student before starting the teaching. The system computes an optimal strategy which represents a way of evolving the student's knowledge from the initial profile. So, the student's knowledge will change progressively to reach the final profile where the teaching objective is judged to be reached. The paper deals with an example presenting a simulation of the result's of a good student and a bad one.
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