Learning Efficiency of Very Simple Grammars from Positive Data

DOI10.1007/978-3-540-75225-7_20zbMath1142.68412OpenAlexW2175053079MaRDI QIDQ3520062

Ryo Yoshinaka

Publication date: 19 August 2008

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-540-75225-7_20

Mathematics Subject Classification ID

Computational learning theory (68Q32) Grammars and rewriting systems (68Q42)

Related Items (4)

Iterative Learning of Simple External Contextual Languages ⋮ Learning indexed families of recursive languages from positive data: A survey ⋮ Resource restricted computability theoretic learning: Illustrative topics and problems ⋮ Learning efficiency of very simple grammars from positive data

Cites Work

• Polynomial-time inference of arbitrary pattern languages
• Grammatical inference for even linear languages based on control sets
• Finding patterns common to a set of strings
• Characteristic sets for polynomial grammatical inference
• Polynomial-time identification of very simple grammars from positive data.
• On polynomial-time learnability in the limit of strictly deterministic automata
• Polynomial-Time Identification of an Extension of Very Simple Grammars from Positive Data
• Inference of Reversible Languages
• Ignoring data may be the only way to learn efficiently
• Algorithmic Learning Theory
• Grammatical Inference: Algorithms and Applications

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