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Algorithmic Learning Theory : Third Workshop, ALT '92 Tokyo, Japan, October 20-22, 1992 Proceedings

Author: S Doshita; Kōichi Furukawa; K P Jantke; Toyaki Nishida
Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 1993.
Series: Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, 743; Lecture notes in computer science., Lecture notes in artificial intelligence ;, 743.
Edition/Format:   eBook : Document : Conference publication : EnglishView all editions and formats
Summary:
This volume contains the papers that were presented at the Third Workshop onAlgorithmic Learning Theory, held in Tokyo in October 1992. In addition to 3invited papers, the volume contains 19 papers accepted for presentation, selected from 29 submitted extended abstracts. The ALT workshops have been held annually since 1990 and are organized and sponsored by the Japanese Society for Artificial Intelligence. The main  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Material Type: Conference publication, Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: S Doshita; Kōichi Furukawa; K P Jantke; Toyaki Nishida
ISBN: 9783540480938 3540480935
OCLC Number: 858926012
Description: 1 online resource (x, 260 pages).
Series Title: Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, 743; Lecture notes in computer science., Lecture notes in artificial intelligence ;, 743.
Responsibility: edited by Shuji Doshita, Koichi Furukawa, Klaus P. Jantke, Toyaki Nishida.

Abstract:

This volume contains the papers that were presented at the Third Workshop onAlgorithmic Learning Theory, held in Tokyo in October 1992. In addition to 3invited papers, the volume contains 19 papers accepted for presentation, selected from 29 submitted extended abstracts. The ALT workshops have been held annually since 1990 and are organized and sponsored by the Japanese Society for Artificial Intelligence. The main objective of these workshops is to provide an open forum for discussions and exchanges of ideasbetween researchers from various backgrounds in this emerging, interdisciplinary field of learning theory. The volume is organized into parts on learning via query, neural networks, inductive inference, analogical reasoning, and approximate learning.

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