Characterization of language learning front informant under various monotonicity constraints

DOI10.1080/09528139408953782zbMath0803.68108OpenAlexW2018407348MaRDI QIDQ4290131

Steffen Lange, Thomas Zeugmann

Publication date: 3 May 1994

Published in: Journal of Experimental & Theoretical Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/09528139408953782

zbMATH Keywords

learning algorithmrecursive languagesmonotonic language learningreference tasks

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Natural language processing (68T50)

Related Items

Learning from Positive Data and Negative Counterexamples: A Survey ⋮ Learning figures with the Hausdorff metric by fractals -- towards computable binary classification ⋮ Learning languages from positive data and negative counterexamples ⋮ Some independence results for control structures in complete numberings ⋮ Monotonic and dual monotonic language learning ⋮ Set-driven and rearrangement-independent learning of recursive languages ⋮ Learning languages and functions by erasing

Cites Work

• Unnamed Item
• Monotonic and non-monotonic inductive inference
• Polynomial-time inference of arbitrary pattern languages
• Prudence and other conditions on formal language learning
• Inductive inference of formal languages from positive data
• Toward a mathematical theory of inductive inference
• A formal theory of inductive inference. Part I
• Language identification in the limit

This page was built for publication: Characterization of language learning front informant under various monotonicity constraints