Handbook of formal languages, vol. 3
Learnable classes of categorial grammars
Learnable classes of categorial grammars
Inference of Reversible Languages
Journal of the ACM (JACM)
Consistent Identification in the Limit of Rigid Grammars from Strings Is NP-hard
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
Some Classes of Regular Languages Identifiable in the Limit from Positive Data
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
What Is the Search Space of the Regular Inference?
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
Consistent Identification in the Limit of Any of the Classes k -Valued Is NP-hard
LACL '01 Proceedings of the 4th International Conference on Logical Aspects of Computational Linguistics
How to Split Recursive Automata
ICGI '08 Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications
Automata and AB-Categorial grammars
CIAA'05 Proceedings of the 10th international conference on Implementation and Application of Automata
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In this paper, we first study the connections between subclasses of AB-categorial grammars and finite state automata. Using this, we explain how learnability results for categorial grammars in Gold's model from structured positive examples translate into regular grammatical inference results from strings. A closer analysis of the generalization operator used in categorial grammar inference shows that it is strictly more powerful than the one used in usual regular grammatical inference, as it can lead outside the class of regular languages. Yet, we show that the result can still be represented by a new kind of finite-state generative model called a recursive automaton. We prove that every unidirectional categorial grammar, and thus every context-free language, can be represented by such a recursive automaton. We finally identify a new subclass of unidirectional categorial grammars for which learning from strings is not more expensive than learning from structures. A drastic simplification of Kanazawa's learning algorithm from strings for this class follows.