Advertisement

A calculus for logical clustering

  • Shuo Bai
Selected Papers Analogical and Inductive Inference
Part of the Lecture Notes in Computer Science book series (LNCS, volume 872)

Abstract

A formal calculus, LC, for logical clustering is proposed in this paper. In addition to conventional first-order logic, a nonmonotonic inference rule for logical clustering is introduced, such that typical forms of induction and analogy are uniformly treated in our theory. Our result shows that the nature of induction and analogy are both “information compression”, that is, the merging of indistinguishable logical symbols. Argumentation games for the implementation of LC are also discussed in this paper.

Key words

Nonmomnotonic reasoning logical clustering argumentation games 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. S. Bai, Reasoning by Argueing: A Game Theoretic Approach, in Automated Reasoning, IFIP Transactions A-19 (Z. Shi Ed.), Elsevier Science Publishers B. V. (NOrth-Holland) 1992, 75–82.Google Scholar
  2. B. Li, Analogical Reasoning: Theory and Implementation. Ph. D. Theses, Beijing Astro, and Aeron. University. 1993.Google Scholar
  3. R. Michalski and R. Stepp, Learning from Observation: Conceptual Clustering, in Machine Learning, Vol. 1, Springer Verlag, 1984.Google Scholar
  4. R. Reiter, A Logic for Default Reasoning. Artificial Intelligence, 13 (1980) 81–132.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • Shuo Bai
    • 1
  1. 1.National Research Center for Intelligent Computing SystemsBeijing BeijingP. R. China

Personalised recommendations