Inference on the Low Level

An Investigation into Deduction, Nonmonotonic Reasoning, and the Philosophy of Cognition

  • HannesĀ Leitgeb

Part of the Applied Logic Series book series (APLS, volume 30)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Introduction

    1. Hannes Leitgeb
      Pages 1-5
  3. Preliminaries

    1. Hannes Leitgeb
      Pages 7-21
  4. The Explication of Monotonic and Nonmonotonic Inference

    1. Front Matter
      Pages 23-23
    2. Hannes Leitgeb
      Pages 25-53
    3. Hannes Leitgeb
      Pages 55-85
  5. The Justification of Monotonic and Nonmonotonic Inference

    1. Front Matter
      Pages 87-87
    2. Hannes Leitgeb
      Pages 121-143
    3. Hannes Leitgeb
      Pages 145-161
  6. The Logic of Justified Monotonic and Nonmonotonic Inference

    1. Front Matter
      Pages 163-163
    2. Hannes Leitgeb
      Pages 189-196
    3. Hannes Leitgeb
      Pages 197-201
    4. Hannes Leitgeb
      Pages 203-207
  7. The Cognition of Justified Monotonic and Nonmonotonic Inference by Low-Level Agents

    1. Front Matter
      Pages 209-209
    2. Hannes Leitgeb
      Pages 211-224
    3. Hannes Leitgeb
      Pages 225-240
    4. Hannes Leitgeb
      Pages 241-260

About this book

Introduction

In contrast to the prevailing tradition in epistemology, the focus in this book is on low-level inferences, i.e., those inferences that we are usually not consciously aware of and that we share with the cat nearby which infers that the bird which she sees picking grains from the dirt, is able to fly. Presumably, such inferences are not generated by explicit logical reasoning, but logical methods can be used to describe and analyze such inferences.

Part 1 gives a purely system-theoretic explication of belief and inference. Part 2 adds a reliabilist theory of justification for inference, with a qualitative notion of reliability being employed. Part 3 recalls and extends various systems of deductive and nonmonotonic logic and thereby explains the semantics of absolute and high reliability. In Part 4 it is proven that qualitative neural networks are able to draw justified deductive and nonmonotonic inferences on the basis of distributed representations. This is derived from a soundness/completeness theorem with regard to cognitive semantics of nonmonotonic reasoning. The appendix extends the theory both logically and ontologically, and relates it to A. Goldman's reliability account of justified belief.

Keywords

epistemology idea logic logical reasoning nonmonotonic reasoning programming reason semantics

Authors and affiliations

  • HannesĀ Leitgeb
    • 1
  1. 1.Department of PhilosophyUniversity of SalzburgAustria

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4020-2806-9
  • Copyright Information Springer Science+Business Media B.V. 2004
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-90-481-6669-5
  • Online ISBN 978-1-4020-2806-9
  • Series Print ISSN 1386-2790
  • About this book