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Conditionals, Information, and Inference

International Workshop, WCII 2002, Hagen, Germany, May 13-15, 2002, Revised Selected Papers

  • Conference proceedings
  • © 2005

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Editors:
  1. Gabriele Kern-Isberner

    1. Dept. of Computer Science, TU Dortmund, Dortmund, Germany

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  2. Wilhelm Rödder

    1. FernUniversität in Hagen, Fachbereich Wirtschaftswissenschaft, Lehrstuhl für BWL, insb. Operations Research, Hagen, Germany

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  3. Friedhelm Kulmann

    1. FernUniversität in Hagen, Fachbereich Wirtschaftswissenschaft, Lehrstuhl BWL, insb. Operations Research, Hagen, Germany

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 3301)

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

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Conference proceedings info: WCII 2002.

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About this book

Conditionals are fascinating and versatile objects of knowledge representation. On the one hand, they may express rules in a very general sense, representing, for example, plausible relationships, physical laws, and social norms. On the other hand, as default rules or general implications, they constitute a basic tool for reasoning, even in the presence of uncertainty. In this sense, conditionals are intimately connected both to information and inference. Due to their non-Boolean nature, however, conditionals are not easily dealt with. They are not simply true or false — rather, a conditional “if A then B” provides a context, A, for B to be plausible (or true) and must not be confused with “A entails B” or with the material implication “not A or B.” This ill- trates how conditionals represent information, understood in its strict sense as reduction of uncertainty. To learn that, in the context A, the proposition B is plausible, may reduce uncertainty about B and hence is information. The ab- ity to predict such conditioned propositions is knowledge and as such (earlier) acquired information. The ?rst work on conditional objects dates back to Boole in the 19th c- tury, and the interest in conditionals was revived in the second half of the 20th century, when the emerging Arti?cial Intelligence made claims for appropriate formaltoolstohandle“generalizedrules.”Sincethen,conditionalshavebeenthe topic of countless publications, each emphasizing their relevance for knowledge representation, plausible reasoning, nonmonotonic inference, and belief revision.

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Table of contents (12 papers)

  1. Front Matter

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  2. Invited Papers

    1. What Is at Stake in the Controversy over Conditionals

      • Ernest W. Adams
      Pages 1-11

    2. Reflections on Logic and Probability in the Context of Conditionals

      • Philip G. Calabrese
      Pages 12-37

    3. Acceptance, Conditionals, and Belief Revision

      • Didier Dubois, Hélène Fargier, Henri Prade
      Pages 38-58

  3. Regular Papers

    1. Getting the Point of Conditionals: An Argumentative Approach to the Psychological Interpretation of Conditional Premises

      • Jean-François Bonnefon, Denis J. Hilton
      Pages 59-64

    2. Projective Default Epistemology

      • Emil Weydert
      Pages 65-85

    3. On the Logic of Iterated Non-prioritised Revision

      • Richard Booth
      Pages 86-107

    4. Assertions, Conditionals, and Defaults

      • Rainer Osswald
      Pages 108-130

    5. A Maple Package for Conditional Event Algebras

      • Piotr Chrzastowski-Wachtel, Jerzy Tyszkiewicz
      Pages 131-151

    6. Conditional Independences in Gaussian Vectors and Rings of Polynomials

      • František Matúš
      Pages 152-161

    7. Looking at Probabilistic Conditionals from an Institutional Point of View

      • Christoph Beierle, Gabriele Kern-Isberner
      Pages 162-179

    8. There Is a Reason for Everything (Probably): On the Application of Maxent to Induction

      • Jeff B. Paris, Alena Vencovská
      Pages 180-199

    9. Completing Incomplete Bayesian Networks

      • Manfred Schramm, Bertram Fronhöfer
      Pages 200-218

  4. Back Matter

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Other volumes

  1. Conditionals, Information, and Inference

Editors and Affiliations

  • Dept. of Computer Science, TU Dortmund, Dortmund, Germany

    Gabriele Kern-Isberner

  • FernUniversität in Hagen, Fachbereich Wirtschaftswissenschaft, Lehrstuhl für BWL, insb. Operations Research, Hagen, Germany

    Wilhelm Rödder

  • FernUniversität in Hagen, Fachbereich Wirtschaftswissenschaft, Lehrstuhl BWL, insb. Operations Research, Hagen, Germany

    Friedhelm Kulmann

Bibliographic Information

  • Book Title: Conditionals, Information, and Inference

  • Book Subtitle: International Workshop, WCII 2002, Hagen, Germany, May 13-15, 2002, Revised Selected Papers

  • Editors: Gabriele Kern-Isberner, Wilhelm Rödder, Friedhelm Kulmann

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/b107184

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2005

  • Softcover ISBN: 978-3-540-25332-7Published: 18 May 2005

  • eBook ISBN: 978-3-540-32235-1Published: 13 May 2005

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XII, 219

  • Topics: Artificial Intelligence, Mathematical Logic and Formal Languages

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