Inductive Inference of Languages from Samplings

Inductive Inference of Context-free Languages - Context-free Expression Method

An inductive inference problem of context-free languages is investigated. There have been many attempts to this problem, and most of them are based on a problem setting in which a representation space for hypotheses is a class of context-free grammars. An inference algorithm given in this paper , on the contrary, employs a kind of extensions of regular expressions called context-free expression...

Context-Free Language Induction by Evolution of Deterministic Push-Down Automata Using Genetic Programming<

The process of learning often consists of Inductive Inference, making generalizations from samples. The problem here is finding generalizations (Grammars) for Formal Languages from finite sets of positive and negative sample sentences. The focus of this paper is on Context-Free Languages (CFL’s) as defined by Context-Free Grammars (CFG’s), some of which are accepted by Deterministic Push-Down A...

Advances in Learning Formal Languages

we present an overview in the advances related to the learning of formal languages i.e. development in the grammatical inference research. The problem of learning correct grammars for the unknown languages is known as grammatical inference. It is considered a main subject of inductive inference, and grammars are important representations to be investigated in machine learning from both theoreti...

Learning Indexed Families of Recursive Languages from Positive Data

In the past 40 years, research on inductive inference has developed along different lines, concerning different formalizations of learning models and in particular of target concepts for learning. One common root of many of these is Gold’s model of identification in the limit. This model has been studied for learning recursive functions, recursively enumerable languages, and recursive languages...

A Negative Result on Inductive Inference of Extended Pattern Languages