Genetic Inference of Finite State Machines
نویسندگان
چکیده
This thesis proposes a methodology based on genetic algorithms for inferring finite state machines. It defines basic parameters like fitness functions and chromosomal representation that can be used with canonical genetic algorithm. Different types of finite state machines can be infered. Several improvements were introduced: inner decimal representation has been used to improve the speed of initialization stage, post–processing stage has been used to remove unaccessible states. The experimental implementaion has also been presented, together with some experiments.
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