Polynomial-Time Identification of Multiple Context-Free Languages from Positive Data and Membership Queries

2010 ◽  
pp. 230-244 ◽  
Author(s):  
Ryo Yoshinaka
Keyword(s):  
Polynomial Time ◽  
Membership Queries ◽  
Positive Data ◽  
Multiple Context ◽  
Context Free

SIMPLE FLAT LANGUAGES: A LEARNABLE CLASS IN THE LIMIT FROM POSITIVE DATA

1999 ◽  
Vol 10 (04) ◽  
pp. 483-501
Author(s):  
OKADOME TAKESI
Keyword(s):  
Polynomial Time ◽  
Arithmetic Progression ◽  
Learning Algorithm ◽  
Finite Elasticity ◽  
Euclidean Algorithm ◽  
Context Sensitive ◽  
Positive Data ◽  
Context Free

The class of simple flat languages defined here is shonw to be learnable in the limit from positive data. In particular, its subclass named k-consecutive, which covers a part of the class of context-sensitive languages not belonging to the class of context-free languages, is polynomial-time learnable in the limit from positive data. The class of "disjunct" unions of simple flat languages is a nontrivial example which is learnable in the limit from positive data, but does not have Wright's finite elasticity. The learning algorithm presented here for identifying the subclasses of flat languages consists essentially of identifying an arithmetic progression in the limit from positive examples using Euclidean algorithm of mutual division.

THE COMPUTATIONAL COMPLEXITY OF THE UNIVERSAL RECOGNITION PROBLEM FOR PARALLEL MULTIPLE CONTEXT-FREE GRAMMARS

1994 ◽  
Vol 10 (4) ◽  
pp. 440-452 ◽  
Author(s):  
Yuichi Kaji1 ◽  
Ryuichi Nakanishi ◽  
Hiroyuki Seki1 ◽  
Tadao Kasami
Keyword(s):  
Computational Complexity ◽  
Recognition Problem ◽  
Multiple Context ◽  
Context Free ◽  
Context Free Grammars
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