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 language | English (US) |
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Pages (from-to) | 21-50 |
Number of pages | 30 |
Journal | Cognitive Science |
Volume | 33 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2009 |
Externally published | Yes |
Keywords
- Bayesian networks
- Casual reasoning
- Semantics of cause
- Structural equations
ASJC Scopus subject areas
- Experimental and Cognitive Psychology
- Cognitive Neuroscience
- Artificial Intelligence