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
Learning regular languages from counterexamples
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
Monotonic and non-monotonic inductive inference
New Generation Computing - Selected papers from the international workshop on algorithmic learning theory,1990
Polynomial-time inference of arbitrary pattern languages
New Generation Computing - Selected papers from the international workshop on algorithmic learning theory,1990
Language learning in dependence on the space of hypotheses
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Rich classes inferable from positive data
Information and Computation
Characterizations of monotonic and dual monotonic language learning
Information and Computation
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)
Inference of Reversible Languages
Journal of the ACM (JACM)
The Power of Vacillation in Language Learning
SIAM Journal on Computing
Theoretical Computer Science
Some Classes of Regular Languages Identifiable in the Limit from Positive Data
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
Characterization of Finite Identification
AII '92 Proceedings of the International Workshop on Analogical and Inductive Inference
Locality, Reversibility, and Beyond: Learning Languages from Positive Data
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
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
LICS '00 Proceedings of the 15th Annual IEEE Symposium on Logic in Computer Science
Automatic learning of subclasses of pattern languages
LATA'11 Proceedings of the 5th 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 learners with feedback queries
Journal of Computer and System Sciences
Robust learning of automatic classes of languages
Journal of Computer and System Sciences
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The present work initiates the study of the learnability of automatic indexable classes which are classes of regular languages of a certain form. Angluin@?s tell-tale condition characterises when these classes are explanatorily learnable. Therefore, the more interesting question is when learnability holds for learners with complexity bounds, formulated in the automata-theoretic setting. The learners in question work iteratively, in some cases with an additional long-term memory, where the update function of the learner mapping old hypothesis, old memory and current datum to new hypothesis and new memory is automatic. Furthermore, the dependence of the learnability on the indexing is also investigated. This work brings together the fields of inductive inference and automatic structures.