Causal reasoning with forces

Causal composition allows people to generate new causal relations by combining existing causal knowledge. We introduce a new computational model of such reasoning, the force theory, which holds that people compose causal relations by simulating the processes that join forces in the world, and compar...

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Bibliographic Details
Published in:Frontiers in human neuroscience 2015-01, Vol.9, p.1-1
Main Authors: Wolff, Phillip, Barbey, Aron K
Format: Article
Language:English
Subjects:
causal learning
causal models
causal reasoning
Causality
Codes
Cognition & reasoning
Computer applications
knowledge structures
lexical semantics
mental simulation
Neuroscience
Psychology
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Summary:Causal composition allows people to generate new causal relations by combining existing causal knowledge. We introduce a new computational model of such reasoning, the force theory, 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., 2014) and the causal model theory (Sloman et al., 2009), 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.
ISSN:1662-5161
1662-5161
DOI:10.3389/fnhum.2015.00001