Inductive inference from positive data is powerful
COLT '90 Proceedings of the third annual workshop on Computational learning theory
Learnable classes of categorial grammars
Learnable classes of categorial grammars
Handbook of Logic and Language
Handbook of Logic and Language
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
Rigid Lambek grammars are not learnable from strings
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Rigid grammars in the associative-commutative Lambek calculus are not learnable
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
k-valued non-associative Lambek categorial grammars are not learnable from strings
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
k-Valued non-associative Lambek grammars are learnable from generalized functor-argument structures
Theoretical Computer Science - Logic, language, information and computation
A bibliographical study of grammatical inference
Pattern Recognition
Good types are useful for learning
Logic and grammar
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In this paper we give some learnability results in the field of categorial grammars. We show that in contrast to k-valued classical categorial grammars, different classes of Lambek grammars are not learnable from strings following Gold's model. The results are obtained by the construction of limit points in each considered class: non associative Lambek grammars with empty sequences and Lambek grammars without empty sequences and without product. Such results express the difficulty of learning categorial grammars from unstructured strings and the need for structured examples.