AbstractDegrees of inferability have been introduced to measure the learning power of inductive inference machines which have access to an oracle. The classical concept of degrees of unsolvability measures the computing power of oracles. In this paper we determine the relationship between both notions
The present paper deals with the learnability of indexed families of uniformly recursive languages b...
Inductive inference machines are algorithmic devices which attempt to synthesize (in the limit) prog...
Ph.D. ThesisInductive inference is a process of hypothesizing a general rule from examples. As a suc...
AbstractDegrees of inferability have been introduced to measure the learning power of inductive infe...
AbstractMost theories of learning consider inferring a function f from either (1) observations about...
AbstractMost theories of learning consider inferring a function f from either (1) observations about...
AbstractThe present work investigates Gold-style algorithmic learning from input–output examples whe...
AbstractA natural ωpLω+1 hierarchy of successively more general criteria of success for inductive in...
AbstractThis paper is concerned with the algorithmic learning, by example in the limit, of programs ...
AbstractThree kinds of restrictions on inductive inference machines (IIMs) are considered: postdicti...
Inductive inference machines are algorithmic devices which attempt to synthesize (in the limit) prog...
In this paper we investigate inductive inference identification criteria which permit infinitely man...
AbstractThis article investigates algorithmic learning, in the limit, of correct programs for recurs...
AbstractIn the past 40 years, research on inductive inference has developed along different lines, e...
AbstractIn this paper the problem of inducing an algorithm for a partial recursive function from the...
The present paper deals with the learnability of indexed families of uniformly recursive languages b...
Inductive inference machines are algorithmic devices which attempt to synthesize (in the limit) prog...
Ph.D. ThesisInductive inference is a process of hypothesizing a general rule from examples. As a suc...
AbstractDegrees of inferability have been introduced to measure the learning power of inductive infe...
AbstractMost theories of learning consider inferring a function f from either (1) observations about...
AbstractMost theories of learning consider inferring a function f from either (1) observations about...
AbstractThe present work investigates Gold-style algorithmic learning from input–output examples whe...
AbstractA natural ωpLω+1 hierarchy of successively more general criteria of success for inductive in...
AbstractThis paper is concerned with the algorithmic learning, by example in the limit, of programs ...
AbstractThree kinds of restrictions on inductive inference machines (IIMs) are considered: postdicti...
Inductive inference machines are algorithmic devices which attempt to synthesize (in the limit) prog...
In this paper we investigate inductive inference identification criteria which permit infinitely man...
AbstractThis article investigates algorithmic learning, in the limit, of correct programs for recurs...
AbstractIn the past 40 years, research on inductive inference has developed along different lines, e...
AbstractIn this paper the problem of inducing an algorithm for a partial recursive function from the...
The present paper deals with the learnability of indexed families of uniformly recursive languages b...
Inductive inference machines are algorithmic devices which attempt to synthesize (in the limit) prog...
Ph.D. ThesisInductive inference is a process of hypothesizing a general rule from examples. As a suc...
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