Skip to main content
SpringerLink
Log in

Algorithmic Learning Theory

9th International Conference, ALT’98, Otzenhausen, Germany, October 8–10, 1998 Proceedings

  • Conference proceedings
  • © 1998

Overview

Editors:
  1. Michael M. Richter

    1. AG Künstliche Intelligenz - Expertensysteme, UniversitÄt Kaiserslautern, Kaiserslautern, Germany

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Carl H. Smith

    1. Department of Computer Science, University of Maryland, College Park, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  3. Rolf Wiehagen

    1. AG Algorithmischesn Lernen, UniversitÄt Kaiserslautern, Kaiserslautern, Germany

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  4. Thomas Zeugmann

    1. Graduate School of Information Science and Electrical Engineering Department of Informatics, Kyushu University, Kassuga, Japan

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 1501)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: ALT 1998.

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (30 papers)

  1. Front Matter

    Pages I-XI
    Download chapter PDF

  2. Editors’ Introduction

    1. Editors’ Introduction

      • Michael M. Richter, Carl H. Smith, Rolf Wiehagen, Thomas Zeugmann
      Pages 1-10

  3. Inductive Logic Programming and Data Mining

    1. Scalability Issues in Inductive Logic Programming

      • Stefan Wrobel
      Pages 11-30

  4. Inductive Inference

    1. Learning to Win Process-Control Games Watching Game-Masters

      • John Case, Matthias Ott, Arun Sharma, Frank Stephan
      Pages 31-45

    2. Closedness Properties in EX-Identification of Recursive Functions

      • Kalvis ApsĪtis, RŪsiņš Freivalds, Raimonds Simanovskis, Juris Smotrovs
      Pages 46-60

  6. Prediction Algorithns

    1. Structured Weight-Based Prediction Algorithms

      • Akira Maruoka, Eiji Takimoto
      Pages 127-142

  7. Inductive Logic Programming

    1. Learning from Entailment of Logic Programs with Local Variables

      • M. R. K. Krishna Rao, A. Sattar
      Pages 143-157

    2. Logical Aspects of Several Bottom-Up Fittings

      • Akihiro Yamamoto
      Pages 158-168

    3. Learnability of Translations from Positive Examples

      • Noriko Sugimoto
      Pages 169-178

    4. Analysis of Case-Based Representability of Boolean Functions by Monotone Theory

      • Ken Satoh
      Pages 179-190

  8. Learning Formal Languages

    1. Locality, Reversibility, and Beyond: Learning Languages from Positive Data

      • Tom Head, Satoshi Kobayashi, Takashi Yokomori
      Pages 191-204

    2. Synthesizing Learners Tolerating Computable Noisy Data

      • John Case, Sanjay Jain
      Pages 205-219

    3. Characteristic Sets for Unions of Regular Pattern Languages and Compactness

      • Masako Sato, Yasuhito Mukouchi, Dao Zheng
      Pages 220-233

    4. Finding a One-Variable Pattern from Incomplete Data

      • Hiroshi Sakamoto
      Pages 234-246

    5. A Fast Algorithm for Discovering Optimal String Patterns in Large Text Databases

      • Hiroki Arimura, Atsushi Wataki, Ryoichi Fujino, Setsuo Arikawa
      Pages 247-261
Back to top

Other volumes

  1. Algorithmic Learning Theory

Keywords

About this book

This volume contains all the papers presented at the Ninth International Con- rence on Algorithmic Learning Theory (ALT’98), held at the European education centre Europ¨aisches Bildungszentrum (ebz) Otzenhausen, Germany, October 8{ 10, 1998. The Conference was sponsored by the Japanese Society for Arti cial Intelligence (JSAI) and the University of Kaiserslautern. Thirty-four papers on all aspects of algorithmic learning theory and related areas were submitted, all electronically. Twenty-six papers were accepted by the program committee based on originality, quality, and relevance to the theory of machine learning. Additionally, three invited talks presented by Akira Maruoka of Tohoku University, Arun Sharma of the University of New South Wales, and Stefan Wrobel from GMD, respectively, were featured at the conference. We would like to express our sincere gratitude to our invited speakers for sharing with us their insights on new and exciting developments in their areas of research. This conference is the ninth in a series of annual meetings established in 1990. The ALT series focuses on all areas related to algorithmic learning theory including (but not limited to): the theory of machine learning, the design and analysis of learning algorithms, computational logic of/for machine discovery, inductive inference of recursive functions and recursively enumerable languages, learning via queries, learning by arti cial and biological neural networks, pattern recognition, learning by analogy, statistical learning, Bayesian/MDL estimation, inductive logic programming, robotics, application of learning to databases, and gene analyses.

Editors and Affiliations

  • AG Künstliche Intelligenz - Expertensysteme, UniversitÄt Kaiserslautern, Kaiserslautern, Germany

    Michael M. Richter

  • Department of Computer Science, University of Maryland, College Park, USA

    Carl H. Smith

  • AG Algorithmischesn Lernen, UniversitÄt Kaiserslautern, Kaiserslautern, Germany

    Rolf Wiehagen

  • Graduate School of Information Science and Electrical Engineering Department of Informatics, Kyushu University, Kassuga, Japan

    Thomas Zeugmann

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation