Abstract
A technique is described for the identification of probabilistic and other nondeterministic automata from sequences of their input/output behaviour. For a given number of states the models obtained are optimal in well defined senses, one related to least-mean-square approximation and the other to Shannon entropy. Practical and theoretical investigations of the technique are outlined.

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