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A beam search algorithm for PFSA inference
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DOI：10.1007/BF01237940.png)
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Abstract
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In the past, many methods have been proposed for the inference of probabilistic and non-probabilistic finite state automata from positive examples of their behaviour. In this paper, we introduce a search method guided by the information-theoretic Minimum Message Length principle to infer Probabilistic Finite State Automata (PFSA).(1) The method is a beam search technique that searches for the best PFSA that accounts for a given dataset. Results of testing this method against some earlier algorithms are presented. A simulated annealing version of the beam search algorithm is also described as ongoing research in the area.
Keywords:
automata inference
information theory
search techniques
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