Automatic learning of subclasses of pattern languages

Authors:
John Case;Sanjay Jain;Trong Dao Le;Yuh Shin Ong;Pavel Semukhin;Frank Stephan
Affiliations:
Department of Computer and Information Sciences, University of Delaware, Newark, DE;Department of Computer Science, National University of Singapore, Singapore, Republic of Singapore;Department of Computer Science, National University of Singapore, Singapore, Republic of Singapore;Department of Computer Science, National University of Singapore, Singapore, Republic of Singapore;Department of Computer Science, University of Regina, Canada;Department of Computer Science, National University of Singapore, Singapore, Republic of Singapore and Department of Mathematics, National University of Singapore, Singapore, Republic of Singapore
Venue:
LATA'11 Proceedings of the 5th international conference on Language and automata theory and applications
Year:
2011

Citing 15
Cited 3

Systems that learn: an introduction to learning theory for cognitive and computer scientists

Systems that learn: an introduction to learning theory for cognitive and computer scientists
Learning regular sets from queries and counterexamples

Information and Computation
Polynomial-time inference of arbitrary pattern languages

New Generation Computing - Selected papers from the international workshop on algorithmic learning theory,1990
Language learning from texts: mindchanges, limited memory, and monotonicity

Information and Computation
On the impact of forgetting on learning machines

Journal of the ACM (JACM)
Incremental learning from positive data

Journal of Computer and System Sciences
Inference of Reversible Languages

Journal of the ACM (JACM)
Polynomial Time Inference of Extended Regular Pattern Languages

Proceedings of RIMS Symposium on Software Science and Engineering
Inductive Inference, DFAs, and Computational Complexity

AII '89 Proceedings of the International Workshop on Analogical and Inductive Inference
Automatic Presentations of Structures

LCC '94 Selected Papers from the International Workshop on Logical and Computational Complexity
Identification of function distinguishable languages

Theoretical Computer Science
Automatic Structures

LICS '00 Proceedings of the 15th Annual IEEE Symposium on Logic in Computer Science
A non-learnable class of E-pattern languages

Theoretical Computer Science - Algorithmic learning theory(ALT 2002)
Learning indexed families of recursive languages from positive data: A survey

Theoretical Computer Science
Learnability of automatic classes

LATA'10 Proceedings of the 4th international conference on Language and Automata Theory and Applications

Automatic learners with feedback queries

CiE'11 Proceedings of the 7th conference on Models of computation in context: computability in Europe
Automatic functions, linear time and learning

CiE'12 Proceedings of the 8th Turing Centenary conference on Computability in Europe: how the world computes
Learnability of automatic classes

Journal of Computer and System Sciences

Quantified Score

Hi-index	0.00

Visualization

Abstract

Automatic classes are classes of languages for which a finite automaton can decide membership question for the languages in the class, in a uniform way, given an index for the language. For alphabet size of at least 4, every automatic class of erasing pattern languages is contained, for some constant n, in the class of all languages generated by patterns which contain (1) every variable only once and (2) at most n symbols after the first occurrence of a variable. It is shown that such a class is automatically learnable using a learner with long-term memory bounded by the length of the first example seen. The study is extended to show the learnability of related classes such as the class of unions of two pattern languages of the above type.