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
Theory of recursive functions and effective computability
Theory of recursive functions and effective computability
Identification of unions of languages drawn from an identifiable class
COLT '89 Proceedings of the second annual workshop on Computational learning theory
The correct definition of finite elasticity: corrigendum to identification of unions
COLT '91 Proceedings of the fourth annual workshop on Computational learning theory
On the intrinsic complexity of learning
Information and Computation
The intrinsic complexity of language identification
Journal of Computer and System Sciences
On the intrinsic complexity of learning recursive functions
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
A Machine-Independent Theory of the Complexity of Recursive Functions
Journal of the ACM (JACM)
Inductive inference of unbounded unions of pattern languages from positive data
Theoretical Computer Science - Special issue on algorithmic learning theory
On Learning Unions of Pattern Languages and Tree Patterns
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
Language Learning From Texts: Degrees of Instrinsic Complexity and Their Characterizations
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
Learning multiple languages in groups
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
Hi-index | 0.00 |
In inductive inference, a machine is given words in a language and the machine is said to identify the language if it correctly names the language. In this paper we study classes of languages where the unions of up to a fixed number (n say) of languages from the class are identifiable. We distinguish between two different scenarios: in one scenario, the learner need only to name the language which results from the union; in the other, the learner must individually name the languages which make up the union (we say that the unioned language is discerningly identified). We define three kinds of identification criteria based on this and by the use of some naturally occurring classes of languages, demonstrate that the inferring power of each of these identification criterion decreases as we increase the number of languages allowed in the union, thus resulting in an infinite hierarchy for each identification criterion. A comparison between the different identification criteria also yielded similar hierarchies. We show that for each n, there exists a class of disjoint languages where all unions of up to n languages from this class can be discerningly identified, but there is no learner which identifies every union of n+1 languages from this class. We give sufficient conditions for classes of languages where the unions can be discerningly identified. We also present language classes which are complete with respect to weak reduction (in terms of intrinsic complexity) for our identification criteria.