On the power of probabilistic strategies in inductive inference

DOI10.1016/0304-3975(83)90067-1zbMath0555.68014OpenAlexW1997380360MaRDI QIDQ760795

Rolf Wiehagen, E. B. Kinber, Rūsiņš Freivalds

Publication date: 1984

Published in: Theoretical Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-3975(83)90067-1

zbMATH Keywords

probabilistic algorithmsTuring machineGödel numberingrecursive functionsinductive inference of programsprobabilistic strategies

Mathematics Subject Classification ID

Related Items (14)

Parallel learning of automatic classes of languages ⋮ Probability and plurality for aggregations of learning machines ⋮ Probabilistic and pluralistic learners with mind changes ⋮ Probabilistic language learning under monotonicity constraints ⋮ Simulating teams with many conjectures ⋮ Learning recursive functions: A survey ⋮ Taming teams with mind changes ⋮ Probabilistic language learning under monotonicity constraints ⋮ Aspects of complexity of probabilistic learning under monotonicity constraints ⋮ Investigations on measure-one identification of classes of languages ⋮ Trade-off among parameters affecting inductive inference ⋮ The synthesis of language learners. ⋮ On the inference of approximate programs ⋮ Training sequences

Cites Work

• Research in the theory of inductive inference by GDR mathematicians - A survey
• Inductive Inference and Computable One‐One Numberings
• The Power of Pluralism for Automatic Program Synthesis
• Toward a mathematical theory of inductive inference
• Inductive inference of automata, functions and programs
• Limiting recursion
• Monadic Elementary Formal Systems
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