Machine Learning, Meta-Reasoning and Logics

  • Pavel B. Brazdil
  • Kurt Konolige

Table of contents

  1. Front Matter
    Pages i-xx
  2. Meta-Reasoning and Machine Learning

    1. Front Matter
      Pages 1-1
    2. D. Paul Benjamin
      Pages 3-17
    3. Stuart J. Russell, Benjamin N. Grosof
      Pages 19-53
    4. Benjamin N. Grosof, Stuart J. Russell
      Pages 55-83
    5. Stuart Russell, Devika Subramanian
      Pages 85-106
    6. Back Matter
      Pages 113-118
  3. Reasoning about Proofs and Explanations

    1. Front Matter
      Pages 119-119
    2. Pavel Brazdil, Peter Clark
      Pages 207-232
  4. Foundations of AI and Machine Learning

    1. Front Matter
      Pages 233-233
    2. Camilla B. Schwind
      Pages 235-255
    3. L. Fariñas del Cerro, A. Herzig
      Pages 301-317
  5. Back Matter
    Pages 319-328

About this book


This book contains a selection of papers presented at the International Workshop Machine Learning, Meta-Reasoning and Logics held in Hotel de Mar in Sesimbra, Portugal, 15-17 February 1988. All the papers were edited afterwards. The Workshop encompassed several fields of Artificial Intelligence: Machine Learning, Belief Revision, Meta-Reasoning and Logics. The objective of this Workshop was not only to address the common issues in these areas, but also to examine how to elaborate cognitive architectures for systems capable of learning from experience, revising their beliefs and reasoning about what they know. Acknowledgements The editing of this book has been supported by COST-13 Project Machine Learning and Knowledge Acquisition funded by the Commission o/the European Communities which has covered a substantial part of the costs. Other sponsors who have supported this work were Junta Nacional de lnvestiga~ao Cientlfica (JNICT), lnstituto Nacional de lnvestiga~ao Cientlfica (INIC), Funda~ao Calouste Gulbenkian. I wish to express my gratitude to all these institutions. Finally my special thanks to Paula Pereira and AnaN ogueira for their help in preparing this volume. This work included retyping all the texts and preparing the camera-ready copy. Introduction 1 1. Meta-Reasoning and Machine Learning The first chapter is concerned with the role meta-reasoning plays in intelligent systems capable of learning. As we can see from the papers that appear in this chapter, there are basically two different schools of thought.


Extension artificial intelligence autonom knowledge learning machine learning nonmonotonic reasoning

Editors and affiliations

  • Pavel B. Brazdil
    • 1
  • Kurt Konolige
    • 2
  1. 1.University of PortoPortugal
  2. 2.SRI InternationalUSA

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag US 1990
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4612-8906-7
  • Online ISBN 978-1-4613-1641-1
  • Series Print ISSN 0893-3405
  • Buy this book on publisher's site
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