Grammatical interface for even linear languages based on control sets
Information Processing Letters
Polynomial-time inference of arbitrary pattern languages
New Generation Computing - Selected papers from the international workshop on algorithmic learning theory,1990
Characteristic Sets for Polynomial Grammatical Inference
Machine Learning
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Journal of the ACM (JACM)
Inductive Inference, DFAs, and Computational Complexity
AII '89 Proceedings of the International Workshop on Analogical and Inductive Inference
Polynomial-time identification of very simple grammars from positive data
Theoretical Computer Science - Selected papers in honour of Setsuo Arikawa
Identification in the limit of substitutable context-free languages
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
Polynomial-time identification of an extension of very simple grammars from positive data
ICGI'06 Proceedings of the 8th international conference on Grammatical Inference: algorithms and applications
Learning indexed families of recursive languages from positive data: A survey
Theoretical Computer Science
Iterative Learning of Simple External Contextual Languages
ALT '08 Proceedings of the 19th international conference on Algorithmic Learning Theory
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The class of very simple grammars is known to be polynomial-time identifiable in the limit from positive data. This paper gives even more general discussion on the efficiency of identification of very simple grammars from positive data, which includes both positive and negative results. In particular, we present an alternative efficient inconsistent learning algorithm for very simple grammars.