Limits of exact algorithms for inference of minimum size finite state machines
We address the problem of selecting the minimum sized finite state machine consistent with given input/output samples. The problem can be solved by computing the minimum finite state machine equivalent to a finite state machine without loops obtained from the training set. We compare the performance of four algorithms for this task: two algorithms for incompletely specified finite state machine reduction, an algorithm based on a well known explicit search procedure and an algorithm based on a new implicit search procedure that is introduced in this paper.
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