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
Language learning in dependence on the space of hypotheses
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
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
Incremental concept learning for bounded data mining
Information and Computation
Inference of Reversible Languages
Journal of the ACM (JACM)
Word Processing in Groups
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
Inductive Inference, DFAs, and Computational Complexity
AII '89 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
Learning indexed families of recursive languages from positive data: A survey
Theoretical Computer Science
An Introduction to Kolmogorov Complexity and Its Applications
An Introduction to Kolmogorov Complexity and Its Applications
Uncountable automatic classes and learning
Theoretical Computer Science
Automatic learners with feedback queries
CiE'11 Proceedings of the 7th conference on Models of computation in context: computability in Europe
Robust learning of automatic classes of languages
ALT'11 Proceedings of the 22nd international conference on Algorithmic learning theory
Learnability of automatic classes
Journal of Computer and System Sciences
Automatic learning of subclasses of pattern languages
Information and Computation
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Automatic classes are classes of languages for which a finite automaton can decide whether a given element is in a set given by its index. The present work studies the learnability of automatic families by automatic learners which, in each round, output a hypothesis and update a long-term memory, depending on the input datum, via an automatic function. Many variants of automatic learners are investigated: where the long-term memory is restricted to be the current hypothesis whenever this exists, cannot be of length larger than the length of the longest datum seen, or has to consist of a constant number of examples seen so far. Learnability is also studied with respect to queries which reveal information about past data or past computation history; the number of queries per round is bounded by a constant.