Automaticity I: properties of a measure of descriptional complexity
Journal of Computer and System Sciences
Handbook of formal languages, vol. 1
Rough set approximations of languages
Fundamenta Informaticae - Special issue: to the memory of Prof. Cecylia Rauszer
Minimal cover-automata for finite languages
Theoretical Computer Science
Minimal Covers of Formal Languages
DLT '01 Revised Papers from the 5th International Conference on Developments in Language Theory
Practical experiments with regular approximation of context-free languages
Computational Linguistics - Special issue on finite-state methods in NLP
Succinct representations of languages by DFA with different levels of reliability
Theoretical Computer Science - Descriptional complexity of formal systems
Approximate recognition of non-regular languages by finite automata
ACSC '05 Proceedings of the Twenty-eighth Australasian conference on Computer Science - Volume 38
Tradeoffs between reliability and conciseness of deterministic finite automata
Journal of Automata, Languages and Combinatorics - Special issue: Selected papers of the fourth international workshop on descriptional complexity of formal systems
Introduction to Automata Theory, Languages, and Computation (3rd Edition)
Introduction to Automata Theory, Languages, and Computation (3rd Edition)
Efficient computation of the relative entropy of probabilistic automata
LATIN'06 Proceedings of the 7th Latin American conference on Theoretical Informatics
Statistical estimation with bounded memory
Statistics and Computing
On Approximating Non-regular Languages by Regular Languages
Fundamenta Informaticae - Theory that Counts: To Oscar Ibarra on His 70th Birthday
Rough Approximations in Varieties of Regular Languages
Fundamenta Informaticae
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We approximate context-free, or more general, languages using finite automata. The degree of approximation is measured, roughly speaking, by counting the number of incorrect answers an automaton gives on inputs of length m and observing how these values behave for large m. More restrictive variants are obtained by requiring that the automaton never accepts words outside the language or that it accepts all words in the language. A further distinction is whether a given (context-free) language has a regular approximation which is optimal under the measure of approximation degree or an approximation which is arbitrarily close to optimal. We study closure and decision properties of the approximation measure.