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Kaufmann, Stefan – Cognitive Science, 2013
The rise of causality and the attendant graph-theoretic modeling tools in the study of counterfactual reasoning has had resounding effects in many areas of cognitive science, but it has thus far not permeated the mainstream in linguistic theory to a comparable degree. In this study I show that a version of the predominant framework for the formal…
Descriptors: Semantics, Linguistic Theory, Form Classes (Languages), Causal Models
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Sloman, Steven A. – Cognitive Science, 2013
Judea Pearl won the 2010 Rumelhart Prize in computational cognitive science due to his seminal contributions to the development of Bayes nets and causal Bayes nets, frameworks that are central to multiple domains of the computational study of mind. At the heart of the causal Bayes nets formalism is the notion of a counterfactual, a representation…
Descriptors: Causal Models, Cognitive Psychology, Cognitive Science, Cognitive Processes
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Sloman, Steven A.; Lagnado, David A. – Cognitive Science, 2005
A normative framework for modeling causal and counterfactual reasoning has been proposed by Spirtes, Glymour, and Scheines (1993; cf. Pearl, 2000). The framework takes as fundamental that reasoning from observation and intervention differ. Intervention includes actual manipulation as well as counterfactual manipulation of a model via thought. To…
Descriptors: Observation, Intervention, Causal Models, Prediction