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Knowledge Representation Techniques

A Rough Set Approach

  • Book
  • © 2006

Overview

Authors:
  1. Patrick Doherty

    1. Department of Computer and Information Science, Linköping University, Sweden

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  2. Witold Łukaszewicz

    1. The University of Economics and Computer Science, Olsztyn, Poland

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  3. Andrzej Skowron

    1. Institute of Mathematics, Warsaw University, Warsaw, Poland

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  4. Andrzej Szałas

    1. Department of Computer and Information Science, Linköping University, Sweden
      The University of Economics and Computer Science, Olsztyn, Poland

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  • Most important feature of our book is a new methodology and new methods for approximate reasoning leading from experimental knowledge (e.g. sensor measurements) to conclusions in natural language. The new results include foundations of our approach built using rough set approach for inducing concept approximations and reasoning with them, methods for embadding background knowledge as well as non-monotonic reasoning in reasoning engines of intelligent systems
  • Readers interested in constructing intelligent systems can learn a novel methodology crucial for development of such systems

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 202)

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Table of contents (15 chapters)

  1. Front Matter

    Pages I-VI
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  2. Introduction and Preliminaries

    1. Front Matter

      Pages I-VI
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    2. Introduction

      • Patrick Doherty, Witold Łukaszewicz, Andrzej Skowron, Andrzej Szałas
      Pages 3-16

    3. Basic Notions

      • Patrick Doherty, Witold Łukaszewicz, Andrzej Skowron, Andrzej Szałas
      Pages 17-38

    4. Rough Sets

      • Patrick Doherty, Witold Łukaszewicz, Andrzej Skowron, Andrzej Szałas
      Pages 39-56

    5. Relational and Deductive Databases

      • Patrick Doherty, Witold Łukaszewicz, Andrzej Skowron, Andrzej Szałas
      Pages 57-76

    6. Non-Monotonic Reasoning

      • Patrick Doherty, Witold Łukaszewicz, Andrzej Skowron, Andrzej Szałas
      Pages 77-99

  3. From Relations to Knowledge Representation

    1. Front Matter

      Pages I-VI
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    2. Rough Knowledge Databases

      • Patrick Doherty, Witold Łukaszewicz, Andrzej Skowron, Andrzej Szałas
      Pages 103-127

    3. Combining Rough and Crisp Knowledge

      • Patrick Doherty, Witold Łukaszewicz, Andrzej Skowron, Andrzej Szałas
      Pages 129-142

    4. Weakest Sufficient and Strongest Necessary Conditions

      • Patrick Doherty, Witold Łukaszewicz, Andrzej Skowron, Andrzej Szałas
      Pages 143-158

    5. CAKE: Computer Aided Knowledge Engineering

      • Patrick Doherty, Witold Łukaszewicz, Andrzej Skowron, Andrzej Szałas
      Pages 159-179

    6. Formalization of Default Logic Using CAKE

      • Patrick Doherty, Witold Łukaszewicz, Andrzej Skowron, Andrzej Szałas
      Pages 181-212

    7. A UAV Scenario: A Case Study

      • Patrick Doherty, Witold Łukaszewicz, Andrzej Skowron, Andrzej Szałas
      Pages 213-226

  4. From Sensors to Relations

    1. Front Matter

      Pages I-VI
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    2. Information Granules

      • Patrick Doherty, Witold Łukaszewicz, Andrzej Skowron, Andrzej Szałas
      Pages 229-243

    3. Tolerance Spaces

      • Patrick Doherty, Witold Łukaszewicz, Andrzej Skowron, Andrzej Szałas
      Pages 245-276

    4. A Rough Set Approach to Machine Learning

      • Patrick Doherty, Witold Łukaszewicz, Andrzej Skowron, Andrzej Szałas
      Pages 277-309

    5. UAV Learning Process: A Case Study

      • Patrick Doherty, Witold Łukaszewicz, Andrzej Skowron, Andrzej Szałas
      Pages 311-320

  5. Back Matter

    Pages 321-342
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Keywords

About this book

1. 1 Background The basis for the material in this book centers around research done in an ongoing long-term project which focuses on the development of highly au- 1 tonomousunmannedaerialvehiclesystems. Theactualplatformwhichserves as a case study for the research in this book will be described in detail later in this chapter. Before doing that, a brief background of the motivations - hind this research will be provided. One of the main research topics in the project is knowledge representation and reasoning and its use in Uav pl- forms. A very strong constraint has been placed on the nature of research done in the project where theoretical results, to the greatest extent possible, should serve as a basis for tractable reasoning mechanisms for use in a fully deployed autonomous Uav operating under soft real-time constraints asso- ated with the types of mission scenarios envisioned. Considering that much of the work with knowledge representation in this context focuses on application domains where one can only hope for an incomplete characterization of such domains, this methodological constraint has proven to be quite challenging since, in essence, the focus is on tractable approximate and nonmonotonic reasoning systems. As is well known, until recently, nonmonotonic formalisms have had a notorious reputation for lack of tractable and scalable reasoning systems.

Reviews

From the reviews:

"Knowledge representation is one of the most important elements of Artificial Intelligence, representing the study of how knowledge about the world can be represented and what kinds of reasoning can be done with that knowledge. The book contains three parts and is founded on the concept of rough sets. … This book is recommended to researchers interested in studying and applying rough set theory in various domains." (Ion Iancu, Zentralblatt MATH, Vol. 1131 (9), 2008)

Authors and Affiliations

  • Department of Computer and Information Science, Linköping University, Sweden

    Patrick Doherty, Andrzej Szałas

  • The University of Economics and Computer Science, Olsztyn, Poland

    Witold Łukaszewicz, Andrzej Szałas

  • Institute of Mathematics, Warsaw University, Warsaw, Poland

    Andrzej Skowron

Bibliographic Information

  • Book Title: Knowledge Representation Techniques

  • Book Subtitle: A Rough Set Approach

  • Authors: Patrick Doherty, Witold Łukaszewicz, Andrzej Skowron, Andrzej Szałas

  • Series Title: Studies in Fuzziness and Soft Computing

  • DOI: https://doi.org/10.1007/3-540-33519-6

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2006

  • Hardcover ISBN: 978-3-540-33518-4Published: 16 June 2006

  • Softcover ISBN: 978-3-642-07012-9Published: 25 November 2010

  • eBook ISBN: 978-3-540-33519-1Published: 31 May 2007

  • Series ISSN: 1434-9922

  • Series E-ISSN: 1860-0808

  • Edition Number: 1

  • Number of Pages: VI, 334

  • Topics: Artificial Intelligence, Mathematical and Computational Engineering, Engineering, general

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