Electronic Resource
Springer
Pattern analysis and applications
1 (1998), S. 121-129
ISSN:
1433-755X
Keywords:
Automata inference
;
Information theory
;
Search techniques
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
Notes:
Abstract 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.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF01237940
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