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Qualitative Spatial Reasoning with Topological Information

  • Jochen Renz

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2293)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 2293)

About this book

Introduction

Spatial knowledge representation and reasoning with spatial knowledge are relevant issues for many application areas such as robotics, geographical information systems, and computer vision. Exceeding purely quantitative approaches, more recently initiated qualitative approaches allow for dealing with spatial information on a more abstract level that is closer to the way humans think and speak.
Starting out with the qualitative, topological constraint calculus RCC8 proposed by Randell, Cui, and Cohn, this work presents answers to a variety of open questions regarding RCC8. The open issues concerning computational properties are solved by exploiting a broad variety of results and methods from logic and theoretical computer science. Questions concerning practical performance are addressed by large-scale empirical computational experiments. The most impressive result is probably the complete classification of computational properties for all fragments of RCC8.

Keywords

Performance classification computer vision information system knowledge knowledge representation robot robotics

Editors and affiliations

  • Jochen Renz
    • 1
  1. 1.Dept.of Computer Science, Database and AI GroupVienna University of TechnologyWienAustria

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-70736-0
  • Copyright Information Springer-Verlag Berlin Heidelberg 2002
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-43346-0
  • Online ISBN 978-3-540-70736-3
  • Series Print ISSN 0302-9743
  • Buy this book on publisher's site
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