Fuzzy rules acquisition using interactive genetic algorithms

This paper mentions fuzzy rules acquisition and their linguistic expressions using the Interactive GA. The number of fuzzy rules is also determined by the presented approach. A fuzzy rule is represented by a chromosome, and individuals with various numbers of chromosomes are operated by the GA operations. Fuzzy sets in acquired fuzzy rules are expressed using plain linguistic labels. The qualitative evaluation of rules intelligibility is attached great importance to as well as the quantitative evaluation by a fitness function. The presented approach is applied to car control for running through crank-typed courses. Simulation results show that the acquired fuzzy rules approach are acceptable from the viewpoints of rules intelligibility, the number of fuzzy rules and control results.