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Qualitative Representation of Spatial Knowledge [electronic resource] / edited by Daniel Hernández.

Contributor(s): Material type: TextTextSeries: Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence ; 804Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 1994Description: XII, 208 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540484257
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q334-342
  • TJ210.2-211.495
Online resources:
Contents:
Qualitativeness -- A cognitive perspective on knowledge representation -- Qualitative representation of positions in 2-D -- Reasoning with qualitative representations -- Applications -- Extensions of the basic model -- Relevant related work -- Conclusion.
In: Springer eBooksSummary: This book develops, for the first time, a qualitative model for the representation of spatial knowledge based only on locative relations between the objects involved. The core of this book is devoted to the study of qualitative inference methods that take into account the rich structure of space. These methods can be applied to quite a number of areas characterized by uncertain or incomplete knowledge, as for example geographic information systems, robot control, computer-aided architectural design, and natural language information systems.
Item type: E-BOOKS
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IMSc Library Link to resource Available EBK6468

Qualitativeness -- A cognitive perspective on knowledge representation -- Qualitative representation of positions in 2-D -- Reasoning with qualitative representations -- Applications -- Extensions of the basic model -- Relevant related work -- Conclusion.

This book develops, for the first time, a qualitative model for the representation of spatial knowledge based only on locative relations between the objects involved. The core of this book is devoted to the study of qualitative inference methods that take into account the rich structure of space. These methods can be applied to quite a number of areas characterized by uncertain or incomplete knowledge, as for example geographic information systems, robot control, computer-aided architectural design, and natural language information systems.

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The Institute of Mathematical Sciences, Chennai, India