Communications of the ACM
Theory of recursive functions and effective computability
Theory of recursive functions and effective computability
Identification of pattern languages from examples and queries
Information and Computation
Learning pattern languages from a single initial example and from queries
COLT '88 Proceedings of the first annual workshop on Computational learning theory
A polynomial-time algorithm for learning k-variable pattern languages from examples
COLT '89 Proceedings of the second annual workshop on Computational learning theory
Polynomial-time inference of arbitrary pattern languages
New Generation Computing - Selected papers from the international workshop on algorithmic learning theory,1990
Decision problems for patterns
Journal of Computer and System Sciences
Learnability of a subclass of extended pattern languages
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
An average-case optimal one-variable pattern language learner
Journal of Computer and System Sciences - Eleventh annual conference on computational learning theory&slash;Twelfth Annual IEEE conference on computational complexity
Introduction to Automata Theory, Languages and Computability
Introduction to Automata Theory, Languages and Computability
Machine Learning
Machine Learning
ICGI '98 Proceedings of the 4th International Colloquium on Grammatical Inference
Polynomial Time Inference of Extended Regular Pattern Languages
Proceedings of RIMS Symposium on Software Science and Engineering
Algorithmic Learning for Knowledge-Based Systems, GOSLER Final Report
Learning Pattern Languages Using Queries
EuroCOLT '97 Proceedings of the Third European Conference on Computational Learning Theory
ALT '97 Proceedings of the 8th International Conference on Algorithmic Learning Theory
ALT '01 Proceedings of the 12th International Conference on Algorithmic Learning Theory
A Negative Result on Inductive Inference of Extended Pattern Languages
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
Learning indexed families of recursive languages from positive data: A survey
Theoretical Computer Science
Hi-index | 0.00 |
A pattern is a finite string of constant and variable symbols. The non-erasing language generated by a pattern is the set of all strings of constant symbols that can be obtained by substituting non-empty strings for variables. In order to build the erasing language generated by a pattern, it is also admissible to substitute the empty string.The present paper deals with the problem of learning erasing pattern languages within Angluin's model of learning with queries. Moreover, the learnability of erasing pattern languages with queries is studied when additional information is available. The results obtained are compared with previously known results in case non-erasing pattern languages have to be learned.First, when regular pattern languages have to be learned, it is shown that the learnability results for the non-erasing case remain valid, if the proper superclass of all erasing regular pattern languages is the object of learning. Second, in the general case, serious differences have been observed. For instance, it turns out that arbitrary erasing pattern languages cannot be learned in settings in which, in the non-erasing case, even polynomially many queries will suffice.