Systems that learn: an introduction to learning theory for cognitive and computer scientists
Systems that learn: an introduction to learning theory for cognitive and computer scientists
Recursively enumerable sets and degrees
Recursively enumerable sets and degrees
Journal of the ACM (JACM)
Hilbert's tenth problem
Subrecursive programming systems: complexity & succinctness
Subrecursive programming systems: complexity & succinctness
Machine learning of higher-order programs
Journal of Symbolic Logic
Breaking the probability 12 barrier in FIN-type learning
Journal of Computer and System Sciences
A recursive introduction to the theory of computation
A recursive introduction to the theory of computation
Classification of predicates and languages
Euro-COLT '93 Proceedings of the first European conference on Computational learning theory
Languages, automata, and logic
Handbook of formal languages, vol. 3
The Power of Pluralism for Automatic Program Synthesis
Journal of the ACM (JACM)
Inductive Inference: Theory and Methods
ACM Computing Surveys (CSUR)
Classification using information
Annals of Mathematics and Artificial Intelligence
On the classification of recursive languages
Information and Computation
Theories of automata on ω-tapes: A simplified approach
Journal of Computer and System Sciences
One-shot learners using negative counterexamples and nearest positive examples
Theoretical Computer Science
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One focus of inductive inference is to infer a program for a function f from observations or queries about f. We propose a new line of research which examines the question of inferring the answers to queries. For a given class of computable functions, we consider the learning (in the limit) of properties of these functions that can be captured by queries formulated in a logical language L. We study the inference types that arise in this context. Of particular interest is a comparison between the learning of properties and the learning of programs. Our results suggest that these two types of learning are incomparable. In addition, our techniques can be used to prove a general lemma about query inference [W. Gasarch, C. Smith, Learning via queries, J. ACM 39 (1992) 649-676]. We show that I@?J@?QI(L)@?QJ(L) for many standard inference types I, J and many query languages L. Hence any separation that holds between these inference types also holds between the corresponding query inference types. One interesting consequence is that[24,49]QEX"0([Succ,@A.