A Causal Model Theory of the Meaning of Cause, Enable, and Prevent

Research output: Contribution to journalArticlepeer-review

Abstract

The verbs cause, enable, and prevent express beliefs about the way the world works. We offer a theory of their meaning in terms of the structure of those beliefs expressed using qualitative properties of causal models, a graphical framework for representing causal structure. We propose that these verbs refer to a causal model relevant to a discourse and that "A causes B" expresses the belief that the causal model includes a link from A to B. "A enables / allows B" entails that the model includes a link from A to B, that A represents a category of events necessary for B, and that an alternative cause of B exists. "A prevents B" entails that the model includes a link from A to B and that A reduces the likelihood of B. This theory is able to account for the results of four experiments as well as a variety of existing data on human reasoning.

Original languageEnglish (US)
Pages (from-to)21-50
Number of pages30
JournalCognitive Science
Volume33
Issue number1
DOIs
StatePublished - Jan 1 2009
Externally publishedYes

Keywords

  • Bayesian networks
  • Casual reasoning
  • Semantics of cause
  • Structural equations

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience
  • Artificial Intelligence

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