Algorithmic learning theory
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Bibliographic Information
Algorithmic learning theory
Ohmsha , Springer-Verlag, c1990
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"The first international workshop on Algorithmic Learning Theory (ALT'90) was held in Tokyo, Oct. 8-10, 1990 ... sponsored by the Japanese Society for Artificial Intelligence, ..." -- Preface
Includes bibliographical references and index
Description and Table of Contents
Description
This volume contains the 31 papers presented at the first international workshop on Algorithmic Learning Theory (ALT '90) which was held in Tokyo, 8-10 October 1990. This workshop was the first meeting on this subject sponsored by the Japanese Society for Artificial Intelligence, and it is expected that future ALT workshops will be held every two years. Recent research on "learning ability" is fundamental to the development of intelligent computer software and of information systems in areas such as natural language understanding, pattern recognition, and robotics. The main aim of this workshop was to provide an open forum for intensive discussions and the exchange of academic information among researchers in the area of algorithmic learning theory. From the 46 extended abstracts submitted, 28 papers were selected for inclusion in this volume, with authors from the USA, the UK, Japan, the USSR, India, and continental Europe. Besides the 28 selected papers, the committee invited 3 lectures by distinguished researchers: "Mathematical Theory of Neural Learning", by S.Amari, University of Tokyo, "Decision Theoretic Generalizations of the PAC Learning Model", by D.Haussler, University of California and "Inductive Logic Programming", by S.
Muggleton, The Turing Institute, Glasgow. This book of proceedings on artificial intelligence, theory of computation and computing methodologies is intended for researchers and postgraduate students.
Table of Contents
28 selected papers divided into the following 6 sections: Neural networks. Concept formation and recognition. Analogical Reasoning. Approximate learning. Inductive inference. New learning paradigms.
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