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date: 21 February 2019

Abstract and Keywords

Causal reasoning belongs to our most central cognitive competencies. Causal knowledge is used as the basis of predictions and diagnoses, categorization, action planning, decision making, and problem solving. Whereas philosophers have analyzed causal reasoning for many centuries, psychologists have for a long time preferred to view causal reasoning and learning as special cases of domain-general competencies, such as logical reasoning or associative learning. The present chapter gives an overview of recent research about causal reasoning. It discusses competing theories, and it contrasts domain-general accounts with theories that model causal reasoning and learning as attempts to make inferences about stable hidden causal processes.

Keywords: causal reasoning, causal learning, causal Bayes nets, causal power, causal mechanisms, associative theories, probabilistic theories, logical theories, force dynamics

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