ICGI '98 Proceedings of the 4th International Colloquium on Grammatical Inference
Learning regular languages using RFSAs
Theoretical Computer Science - Special issue: Algorithmic learning theory
Universal automata and NFA learning
Theoretical Computer Science
Inference improvement by enlarging the training set while learning DFAs
CIARP'05 Proceedings of the 10th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis and Applications
A family of algorithms for non deterministic regular languages inference
CIAA'06 Proceedings of the 11th international conference on Implementation and Application of Automata
Minimalizations of NFA using the universal automaton
CIAA'04 Proceedings of the 9th international conference on Implementation and Application of Automata
A randomised inference algorithm for regular tree languages
Natural Language Engineering
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A new general method for inference of regular languages using nondeterministic automata as output has recently been developed and proved to converge. The aim of this paper is to describe and analyze the behavior of two implementations of that method and to compare it with two well known algorithms for the same task. A complete set of experiments has been carried out and the results of the new algorithms improve the existing ones both in recognition rates as in sizes of the output automata.