Synthesizing inductive expertise

DOI10.1016/0890-5401(88)90055-7zbMath0652.68068OpenAlexW2059655876MaRDI QIDQ1107325

Michael Stob, Scott Weinstein, Daniel N. Osherson

Publication date: 1988

Published in: Information and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0890-5401(88)90055-7

zbMATH Keywords

inductive inferencerecursion theorysynthesizers

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (11)

The complexity of universal text-learners ⋮ An approach to intrinsic complexity of uniform learning ⋮ Paradigms of truth detection ⋮ Separation of uniform learning classes. ⋮ Robust learning with infinite additional information ⋮ Synthesizing noise-tolerant language learners ⋮ Synthesizing learners tolerating computable noisy data ⋮ Increasing the power of uniform inductive learners ⋮ Learning algebraic structures from text ⋮ The synthesis of language learners. ⋮ The complexity of universal text-learners.

Cites Work

• Comparison of identification criteria for machine inductive inference
• Inductive inference of formal languages from positive data
• Toward a mathematical theory of inductive inference
• Language identification in the limit

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