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Book cover
  • Conference proceedings
  • © 1994

Knowledge Representation and Reasoning Under Uncertainty

Logic at Work

Editors:

  1. Michael Masuch
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  2. László Pólos
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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 808)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Conference series link(s): LaW: International Conference on Logic at Work

Conference proceedings info: Logic at Work 1992.

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Table of contents (14 papers)

  1. Front Matter

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  2. The role of expectations in reasoning

    • Peter Gärdenfors
    Pages 1-16

  3. On logics of approximate reasoning

    • Petr Hájek
    Pages 17-29

  4. Gentzen sequent calculus for possibilistic reasoning

    • Churn Jung Liau, Bertrand I -Peng Lin
    Pages 31-40

  5. A model of inductive reasoning

    • Peter A. Flach
    Pages 41-56

  6. Automated reasoning with uncertainties

    • Flávio S. Corrêa da Silva, Dave S. Robertson, Jane Hesketh
    Pages 57-79

  8. Contradiction removal semantics with explicit negation

    • Luís Moniz Pereira, José J. Alferes, Joaquim N. Aparício
    Pages 91-105

  9. Logic programming for non-monotonic reasoning

    • Luís Moniz Pereira, Joaquim N. Aparício, José J. Alferes
    Pages 107-121

  12. Knowledge theoretic properties of topological spaces

    • Konstantinos Georgatos
    Pages 147-159

  13. Rough logic for multi-agent systems

    • Cecylia M. Rauszer
    Pages 161-181

  14. A logical approach to multi-sources reasoning

    • Laurence Cholvy
    Pages 183-196

  15. Situation theory and social structure

    • Keith Devlin
    Pages 197-237

  16. Back Matter

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Other Volumes

  1. Knowledge Representation and Reasoning Under Uncertainty

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About this book

This volume is based on the International Conference Logic at Work, held in Amsterdam, The Netherlands, in December 1992. The 14 papers in this volume are selected from 86 submissions and 8 invited contributions and are all devoted to knowledge representation and reasoning under uncertainty, which are core issues of formal artificial intelligence.
Nowadays, logic is not any longer mainly associated to mathematical and philosophical problems. The term applied logic has a far wider meaning, as numerous applications of logical methods, particularly in computer science, artificial intelligence, or formal linguistics, testify. As demonstrated also in this volume, a variety of non-standard logics gained increased importance for knowledge representation and reasoning under uncertainty.
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Keywords

  • Artificial intelligence
  • intelligence
  • knowledge
  • knowledge representation
  • linguistics
  • logic
  • uncertainty
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Bibliographic Information

  • Book Title: Knowledge Representation and Reasoning Under Uncertainty

  • Book Subtitle: Logic at Work

  • Editors: Michael Masuch, László Pólos

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/3-540-58095-6

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag Berlin Heidelberg 1994

  • Softcover ISBN: 978-3-540-58095-9Published: 28 June 1994

  • eBook ISBN: 978-3-540-48451-6Published: 06 July 2005

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: X, 242

  • Topics: Artificial Intelligence, Mathematics, Formal Languages and Automata Theory

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Softcover Book USD 99.00
Price excludes VAT (USA)
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