Learning via queries in [+, <]

DOI10.2307/2275176zbMath0774.03023OpenAlexW2117977375MaRDI QIDQ4008746

Mark G. Pleszkoch, Robert M. Solovay, William I. Gasarch

Publication date: 27 September 1992

Published in: Journal of Symbolic Logic (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/2275176

zbMATH Keywords

recursive functionsinductive inference machineeffective procedures for quantifier eliminationquery inductive inference

Mathematics Subject Classification ID

Decidability of theories and sets of sentences (03B25) Complexity of computation (including implicit computational complexity) (03D15) First-order arithmetic and fragments (03F30) Recursive functions and relations, subrecursive hierarchies (03D20) Turing machines and related notions (03D10) Quantifier elimination, model completeness, and related topics (03C10)

Related Items (8)

Refuting learning revisited. ⋮ Recursion theoretic models of learning: Some results and intuitions ⋮ Inferring answers to queries ⋮ Taming teams with mind changes ⋮ Automatic learning from positive data and negative counterexamples ⋮ One-shot learners using negative counterexamples and nearest positive examples ⋮ Learning via queries and oracles ⋮ Automata techniques for query inference machines

Cites Work

• Comparison of identification criteria for machine inductive inference
• Probability and plurality for aggregations of learning machines
• Saving the phenomena: Requirements that inductive inference machines not contradict known data
• On the complexity of inductive inference
• The Power of Pluralism for Automatic Program Synthesis
• Language identification in the limit

This page was built for publication: Learning via queries in [+, <]