Logic versus Approximation

Essays Dedicated to Michael M. Richter on the Occasion of his 65th Birthday

  • Wolfgang Lenski

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3075)

Table of contents

About this book


Nowadays knowledge-based systems research and development essentially employs two paradigms of reasoning. There are on the one hand the logic-based approaches where logic is to be understood in a rather broad sense; usually these approaches are used in symbolic domains where numerical calculations are not the core challenge. On the other hand we find approximation oriented reasoning; methods of these kinds are mainly applied in numerical domains where approximation is part of the scientific methodology itself.

However, from an abstract level all these approaches do focus on similar topics and arise on various levels such as problem modeling, inference and problem solving techniques, algorithms and mathematical methods, mathematical relations between discrete and continuous properties, and are integrated in tools and applications. In accordance with the unifying vision and research interest of Michael M. Richter and in correspondence to his scientific work, this book presents 13 revised full papers advocating the integration of logic-based and approximation-oriented approaches in knowledge processing.


Fuzzy agile software development algorithms fuzzy logic fuzzy predicate logic knowledge sharing knowledge-based system knowledge-based systems logic modeling optimization programming quantified Boolean formulas similarity search symbolic computing

Editors and affiliations

  • Wolfgang Lenski
    • 1
  1. 1.Department of Computer ScienceUniversity of KaiserslauternKaiserslautern

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2004
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-22562-1
  • Online ISBN 978-3-540-25967-1
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
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