Causal reasoning with forces
Identifieur interne : 000A65 ( Main/Exploration ); précédent : 000A64; suivant : 000A66Causal reasoning with forces
Auteurs : Phillip Wolff [États-Unis] ; Aron K. Barbey [États-Unis]Source :
- Frontiers in Human Neuroscience [ 1662-5161 ] ; 2015.
Abstract
Causal composition allows people to generate new causal relations by combining existing causal knowledge. We introduce a new computational model of such reasoning, the
Url:
DOI: 10.3389/fnhum.2015.00001
PubMed: 25653611
PubMed Central: 4301188
Affiliations:
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<front><div type="abstract" xml:lang="en"><p>Causal composition allows people to generate new causal relations by combining existing causal knowledge. We introduce a new computational model of such reasoning, the <italic>force theory</italic>
, which holds that people compose causal relations by simulating the processes that join forces in the world, and compare this theory with the mental model theory (Khemlani et al., <xref rid="B39" ref-type="bibr">2014</xref>
) and the causal model theory (Sloman et al., <xref rid="B60" ref-type="bibr">2009</xref>
), which explain causal composition on the basis of mental models and structural equations, respectively. In one experiment, the force theory was uniquely able to account for people's ability to compose causal relationships from complex animations of real-world events. In three additional experiments, the force theory did as well as or better than the other two theories in explaining the causal compositions people generated from linguistically presented causal relations. Implications for causal learning and the hierarchical structure of causal knowledge are discussed.</p>
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