Logic, Probability, and Human Reasoning

Abstract

This review addresses the long-standing puzzle of how logic and probability fit together in human reasoning. Many cognitive scientists argue that conventional logic cannot underlie deductions, because it never requires valid conclusions to be withdrawn not even if they are false; it treats conditional assertions implausibly; and it yields many vapid, although valid, conclusions. A new paradigm of probability logic allows conclusions to be withdrawn and treats conditionals more plausibly, although it does not address the problem of vapidity. The theory of mental models solves all of these problems. It explains how people reason about probabilities and postulates that the machinery for reasoning is itself probabilistic. Recent investigations accordingly suggest a way to integrate probability and deduction.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2015
Accession Number
ADA620521

Entities

People

  • Geoffrey P. Goodwin
  • P. N. Johnson-laird
  • Sangeet S. Khemlani

Organizations

  • United States Naval Research Laboratory

Tags

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Causal Reasoning
  • Cognition
  • Cognitive Science
  • Computer Programming
  • Computer Programs
  • Computers
  • Judgment
  • Language
  • Materials
  • Model Theory
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Psychology
  • Reasoning
  • Thinking

Fields of Study

  • Philosophy

Readers

  • Artificial Intelligence