We consider inductive inference of formal languages, as defined by Gold (1967), in the case of positive data, i.e., when the examples of a given formal language are successive elements of some arbitrary enumeration of the elements of the language. We prove a theorem characterizing when an indexed family of nonempty recursive formal languages is inferrable from positive data. From this theorem we obtain other useful conditions for inference from positive data, and give several examples of their application. We give counterexamples to two variants of the characterizing condition, and investigate conditions for inference from positive data that avoids “overgeneralization.
AbstractThe pattern languages are languages that are generated from patterns, and were first propose...
Proc. ALT\u2790, 339-354; New Generation Computing 8, 371-384, 1991A formal system is a finite set o...
Abstract In this paper, we study inductive inference of a subclass of Prolog programs from positive ...
We consider inductive inference of formal languages, as defined by Gold (1967), in the case of posit...
The present paper deals with the learnability of indexed families of uniformly recursive languages b...
Inductive inference of a language L from negative data is the one based only on words not in L. In o...
A formal system, we deal with in this paper, is a set of formulas of the form $ P_1(t_1) leftarrow P...
AbstractInductive inference from positive data is shown to be remarkably powerful using the framewor...
AbstractIn the past 40 years, research on inductive inference has developed along different lines, e...
AbstractIn this paper, we study inferability of Prolog programs from positive examples alone. The im...
This thesis focuses on the Gold model of inductive inference from positive data. There are several ...
AbstractA pattern is a string consisting of constant symbols and variables. The language of a patter...
Inductive inference of a language $ L $ from negative data is the one based only on words not in $ L...
This paper develops a mathematical theory of language identification from a set theoretic viewpoint....
Language learnability is investigated in the Gold paradigm of inductive inference from positive dat...
AbstractThe pattern languages are languages that are generated from patterns, and were first propose...
Proc. ALT\u2790, 339-354; New Generation Computing 8, 371-384, 1991A formal system is a finite set o...
Abstract In this paper, we study inductive inference of a subclass of Prolog programs from positive ...
We consider inductive inference of formal languages, as defined by Gold (1967), in the case of posit...
The present paper deals with the learnability of indexed families of uniformly recursive languages b...
Inductive inference of a language L from negative data is the one based only on words not in L. In o...
A formal system, we deal with in this paper, is a set of formulas of the form $ P_1(t_1) leftarrow P...
AbstractInductive inference from positive data is shown to be remarkably powerful using the framewor...
AbstractIn the past 40 years, research on inductive inference has developed along different lines, e...
AbstractIn this paper, we study inferability of Prolog programs from positive examples alone. The im...
This thesis focuses on the Gold model of inductive inference from positive data. There are several ...
AbstractA pattern is a string consisting of constant symbols and variables. The language of a patter...
Inductive inference of a language $ L $ from negative data is the one based only on words not in $ L...
This paper develops a mathematical theory of language identification from a set theoretic viewpoint....
Language learnability is investigated in the Gold paradigm of inductive inference from positive dat...
AbstractThe pattern languages are languages that are generated from patterns, and were first propose...
Proc. ALT\u2790, 339-354; New Generation Computing 8, 371-384, 1991A formal system is a finite set o...
Abstract In this paper, we study inductive inference of a subclass of Prolog programs from positive ...