Inductive inference, DFAs, and computational complexity Page 1 Inductive Inference, DFAs, and
Computational Complexity Leonard Pitt* Department of Computer Science University of Illinois …

In this paper, we provide a survey of recent advances in the field “Grammatical Inference”
with a particular emphasis on the results concerning the learnability of target classes …

At a time of unprecedented expansion in the life sciences, evolution is the one theory that
transcends all of biology. Any observation of a living system must ultimately be interpreted in …

The problem of inducing, learning or inferring grammars has been studied for decades, but
only in recent years has grammatical inference emerged as an independent field with …

This is the first comprehensive introduction to computational learning theory. The author's
uniform presentation of fundamental results and their applications offers AI researchers a …

We consider the problem of exact identification of classes of concepts using only
equivalence queries. We define a combinatorial property, approximate fingerprints, of …

The field of grammatical inference (also known as grammar induction) is transversal to a
number of research areas including machine learning, formal language theory, syntactic and …

Not now! This also is part of the goals. So far the emphasis has been on inductive
learning(from examples) of concepts (binary classifications of examples) adapting the …

We describe a framework for inducing probabilistic grammars from corpora of positive
samples. First, samples are incorporated by adding ad-hoc rules to a working grammar; …

The general topic of this thesis is the probabilistic modeling of language, in particular natural
language. In probabilistic language modeling, one characterizes the strings of phonemes …