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Mathematical Models of Category-Based Induction

  • Mizuho Mishima
  • Makoto Kikuchi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4265)

Abstract

Category-based induction is a kind of inductive reasoning in which the premise and the conclusion of the argument is in the form all the member of a category have the property. Rips and Osherson et al. investigated the argument strength of category-based induction, and Lopez et al. showed that there are differences of the acceptability of category-based induction between infants and growing-ups. There are two problems in their analysis. One is the ambiguity of the difference between categories and individuals, and the other is the reason of the changes of the acceptability in developmental process of logical inference. In this paper we give mathematical models category-based induction and, based on the models, propose a hypothesis which explains the reason of the problems.

Keywords

Inductive Reasoning Logical Inference Premise Diversity Naive Model Argument Strength 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Mizuho Mishima
    • 1
  • Makoto Kikuchi
    • 2
  1. 1.Department of Information and Media ScienceKobe UniversityKobeJapan
  2. 2.Department of Computer and Systems EngineeringKobe UniversityKobeJapan

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