Automated Model Building

  • Ricardo Caferra
  • Alexander Leitsch
  • Nicholas Peltier

Part of the Applied Logic Series book series (APLS, volume 31)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Ricardo Caferra, Alexander Leitsch, Nicholas Peltier
    Pages 1-17
  3. Ricardo Caferra, Alexander Leitsch, Nicholas Peltier
    Pages 19-42
  4. Ricardo Caferra, Alexander Leitsch, Nicholas Peltier
    Pages 43-150
  5. Ricardo Caferra, Alexander Leitsch, Nicholas Peltier
    Pages 151-232
  6. Ricardo Caferra, Alexander Leitsch, Nicholas Peltier
    Pages 233-272
  7. Ricardo Caferra, Alexander Leitsch, Nicholas Peltier
    Pages 273-318
  8. Ricardo Caferra, Alexander Leitsch, Nicholas Peltier
    Pages 319-320
  9. Back Matter
    Pages 321-344

About this book

Introduction

On the history of the book: In the early 1990s several new methods and perspectives in au- mated deduction emerged. We just mention the superposition calculus, meta-term inference and schematization, deductive decision procedures, and automated model building. It was this last ?eld which brought the authors of this book together. In 1994 they met at the Conference on Automated Deduction (CADE-12) in Nancy and agreed upon the general point of view, that semantics and, in particular, construction of models should play a central role in the ?eld of automated deduction. In the following years the deduction groups of the laboratory LEIBNIZ at IMAG Grenoble and the University of Technology in Vienna organized several bilateral projects promoting this topic. This book emerged as a main result of this cooperation. The authors are aware of the fact, that the book does not cover all relevant methods of automated model building (also called model construction or model generation); instead the book focuses on deduction-based symbolic methods for the construction of Herbrand models developed in the last 12 years. Other methods of automated model building, in particular also ?nite model building, are mainly treated in the ?nal chapter; this chapter is less formal and detailed but gives a broader view on the topic and a comparison of di?erent approaches. Howtoreadthisbook: In the introduction we give an overview of automated deduction in a historical context, taking into account its relationship with the human views on formal and informal proofs.

Keywords

artificial intelligence automated deduction intelligence logic

Authors and affiliations

  • Ricardo Caferra
    • 1
  • Alexander Leitsch
    • 2
  • Nicholas Peltier
    • 3
  1. 1.Laboratory Leibniz — IMAG, INPGGrenobleFrance
  2. 2.Vienna University of TechnologyAustria
  3. 3.Laboratory Leibniz — IMAG, CNRSGrenobleFrance

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4020-2653-9
  • Copyright Information Springer Science+Business Media B.V. 2004
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-90-481-6696-1
  • Online ISBN 978-1-4020-2653-9
  • Series Print ISSN 1386-2790
  • About this book