In this paper, the computational problem of finding a pattern descriptive of a given sample is studied and a polynomial-time algorithm is proposed to solve the problem.Expand

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 language are successive elements of some arbitrary enumeration of the elements of the language.Expand

A famdy of efficient algorithms for referring certain subclasses of the regular languages from fmtte posttwe samples is presented These subclasses are the k-reversible languages, for k = 0, 1, 2, 3, 4, 5, 6.Expand

We consider the problem of using queries to learn an unknown concept. Several types of queries are described and studied: membership, equivalence, subset, superset, disjointness, and exhaustiveness… Expand

The basic question addressed in this paper is: how can a learning algorithm cope with incorrect training examples? Specifically, how can algorithms that produce an “approximately correct”… Expand

We describe and analyse three simple efficient algorithms with good probabilistic behaviour; two algorithms with run times of O ( n (log n ) 2 ) which almost certainly find directed (undirected) Hamiltonian circuits in random graphs of at least cn log n edges, and an algorithm with a run time of O( n log n ) that almost certainly finds a perfect matching in a random graph.Expand

This survey highlights and explains the main ideas that have been developed in the study of inductive inference, with special emphasis on the relations between the general theory and the implementations.Expand