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
Learning in the presence of inaccurate information
Theoretical Computer Science
Learning approximately regular languages with reversible languages
Theoretical Computer Science
Handbook of formal languages, vol. 1: word, language, grammar
Handbook of formal languages, vol. 1: word, language, grammar
Handbook of formal languages, vol. 1
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
Polynomial Time Inference of Extended Regular Pattern Languages
Proceedings of RIMS Symposium on Software Science and Engineering
STACS '94 Proceedings of the 11th Annual Symposium on Theoretical Aspects of Computer Science
Inductive Inference of an Approximate Concept from Positive Data
AII '94 Proceedings of the 4th International Workshop on Analogical and Inductive Inference: Algorithmic Learning Theory
On Approximately Identifying Concept Classes in the Limit
ALT '95 Proceedings of the 6th International Conference on Algorithmic Learning Theory
Identification of function distinguishable languages
Theoretical Computer Science
A non-learnable class of E-pattern languages
Theoretical Computer Science - Algorithmic learning theory(ALT 2002)
Discontinuities in pattern inference
Theoretical Computer Science
Learning and extending sublanguages
Theoretical Computer Science
Developments from enquiries into the learnability of the pattern languages from positive data
Theoretical Computer Science
Theoretical Computer Science
Bad news on decision problems for patterns
Information and Computation
Uncountable automatic classes and learning
ALT'09 Proceedings of the 20th international conference on Algorithmic learning theory
Existence and nonexistence of descriptive patterns
Theoretical Computer Science
Fast learning of restricted regular expressions and DTDs
Proceedings of the 16th International Conference on Database Theory
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In the present paper, we introduce a variant of Gold-style learners that is not required to infer precise descriptions of the languages in a class, but that must find descriptive patterns, i.e., optimal generalisations within a class of pattern languages. Our first main result characterises those indexed families of recursive languages that can be inferred by such learners, and we demonstrate that this characterisation shows enlightening connections to Angluin@?s corresponding result for exact inference. Furthermore, this result reveals that our model can be interpreted as an instance of a natural extension of Gold@?s model of language identification in the limit. Using a notion of descriptiveness that is restricted to the natural subclass of terminal-free E-pattern languages, we introduce a generic inference strategy, and our second main result characterises those classes of languages that can be generalised by this strategy. This characterisation demonstrates that there are major classes of languages that can be generalised in our model, but not be inferred by a normal Gold-style learner. Our corresponding technical considerations lead to insights of intrinsic interest into combinatorial and algorithmic properties of pattern languages.