TY - GEN

T1 - Learning concatenations of locally testable languages from positive data

AU - Kobayashi, Satoshi

AU - Yokomori, Takashi

PY - 1994

Y1 - 1994

N2 - This paper introduces the class of concatenations of locally testable languages and its subclasses, and presents some results on the learnability of the classes from positive data. We first establish several relationships among the language classes introduced, and give a sufficient condition for a concatenation operation to preserve finite elasticity of a language class C. Then we show that, for each k, the class CLT≤k, a subclass of concatenations of locally testable languages, is identifiable in the limit from positive data. Further, we introduce a notion of local parsability, and define a class (k, l)-CLTS, which is a subclass of the class of concatenations of strictly locally testable languages. Then, for each k, l ≥ 1, (k, l)-CLTS is proved to be identifiable in the limit from positive data using reversible automata with the conjectures updated in polynomial time. Some possible applications of this result are also briefly discussed.

AB - This paper introduces the class of concatenations of locally testable languages and its subclasses, and presents some results on the learnability of the classes from positive data. We first establish several relationships among the language classes introduced, and give a sufficient condition for a concatenation operation to preserve finite elasticity of a language class C. Then we show that, for each k, the class CLT≤k, a subclass of concatenations of locally testable languages, is identifiable in the limit from positive data. Further, we introduce a notion of local parsability, and define a class (k, l)-CLTS, which is a subclass of the class of concatenations of strictly locally testable languages. Then, for each k, l ≥ 1, (k, l)-CLTS is proved to be identifiable in the limit from positive data using reversible automata with the conjectures updated in polynomial time. Some possible applications of this result are also briefly discussed.

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U2 - 10.1007/3-540-58520-6_80

DO - 10.1007/3-540-58520-6_80

M3 - Conference contribution

AN - SCOPUS:49649102787

SN - 9783540585206

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 407

EP - 422

BT - Algorithmic Learning Theory - 4th International Workshop on Analogical and Inductive Inference, AII 1994 and 5th International Workshop on Algorithmic Learning Theory, ALT 1994, Proceedings

A2 - Arikawa, Setsuo

A2 - Jantke, Klaus P.

PB - Springer Verlag

T2 - 4th International Workshop on Analogical and Inductive Inference, AII 1994 and 5th International Workshop on Algorithmic Learning Theory, ALT 1994

Y2 - 10 October 1994 through 15 October 1994

ER -