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Analogical and Inductive Inference

International Workshop AII'86 Wendisch-Rietz, GDR, October 6-10, 1986, Proceedings

  • Conference proceedings
  • © 1987

Overview

Editors:
  1. Klaus P. Jantke
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 265)

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Table of contents (16 papers)

  1. Front Matter

    Download chapter PDF

  2. Towards the development of an analysis of learning algorithms

    • Robert P. Daley
    Pages 1-18

  3. Using the algorithm of analogy for generation of robot programs

    • V. Bauche
    Pages 19-22

  4. On the inference of sequences of functions

    • William I. Gasarch, Carl H. Smith
    Pages 23-41

  5. Fixed point equations as hypotheses in inductive reasoning

    • T. Gergely, Zs. Szabó
    Pages 42-54

  6. Inductive inference of functions from noised observations

    • Jan Grabowski
    Pages 55-60

  7. Reasoning by analogy as a partial identity between models

    • Makoto Haraguchi, Setsuo Arikawa
    Pages 61-87

  8. Can missing information be also useful?

    • A. Juhos
    Pages 88-104

  9. A decidability problem of church-rosser specifications for program synthesis

    • Steffen Lange
    Pages 105-124

  10. Some considerations about formalization of analogical reasoning

    • Ch. Melis, E. Melis
    Pages 125-134

  11. Analogical reasoning using graph transformations

    • D. Pötschke
    Pages 135-144

  12. Knowledge acquisition by inductive learning from examples

    • Joachim Selbig
    Pages 145-163

  13. On the inference of programs approximately computing the desired function

    • Carl H. Smith, Mahendran Velauthapillai
    Pages 164-176

  14. Stratified inductive hypothesis generation

    • ZS. Szabó
    Pages 177-195

  15. A model theoretic oriented approach to analogy

    • Helmut Thiele
    Pages 196-208

  16. On the complexity of effective program synthesis

    • Rolf Wiehagen
    Pages 209-219

  17. On barzdin's conjecture

    • Thomas Zeugmann
    Pages 220-227
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Keywords

About this book

This volume contains revised versions of presentations at the International Workshop on Analogical and Inductive Inference (AII '86) held in Wendisch-Rietz, GDR, October 16-10, 1986. Inductive inference and analogical reasoning are two basic approaches to learning algorithms. Both allow for exciting problems and promising concepts of invoking deeper mathematical results for considerable advances in intelligent software systems. Hence analogical and inductive inference may be understood as a firm mathematical basis for a large variety of problems in artificial intelligence. While the papers on inductive inference contain technical results and reflect the state of the art of this well-developed mathematical theory, those devoted to analogical reasoning reflect the ongoing process of developing the basic concepts of the approach. The workshop thus contributes significantly to the advancement of this field.

Bibliographic Information

  • Book Title: Analogical and Inductive Inference

  • Book Subtitle: International Workshop AII'86 Wendisch-Rietz, GDR, October 6-10, 1986, Proceedings

  • Editors: Klaus P. Jantke

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/3-540-18081-8

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag Berlin Heidelberg 1987

  • Softcover ISBN: 978-3-540-18081-4Published: 15 July 1987

  • eBook ISBN: 978-3-540-47739-6Published: 02 July 2005

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: VIII, 232

  • Topics: Artificial Intelligence

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