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  1. Causal Networks or Causal Islands? The Representation of Mechanisms and the Transitivity of Causal Judgment.Samuel G. B. Johnson & Woo-Kyoung Ahn - 2015 - Cognitive Science 39 (7):1468-1503.
    Knowledge of mechanisms is critical for causal reasoning. We contrasted two possible organizations of causal knowledge—an interconnected causal network, where events are causally connected without any boundaries delineating discrete mechanisms; or a set of disparate mechanisms—causal islands—such that events in different mechanisms are not thought to be related even when they belong to the same causal chain. To distinguish these possibilities, we tested whether people make transitive judgments about causal chains by inferring, given A causes B and B causes C, (...)
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  • Hierarchical Bayesian models as formal models of causal reasoning.York Hagmayer & Ralf Mayrhofer - 2013 - Argument and Computation 4 (1):36 - 45.
    (2013). Hierarchical Bayesian models as formal models of causal reasoning. Argument & Computation: Vol. 4, Formal Models of Reasoning in Cognitive Psychology, pp. 36-45. doi: 10.1080/19462166.2012.700321.
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  • Causal Responsibility and Robust Causation.Guy Grinfeld, David Lagnado, Tobias Gerstenberg, James F. Woodward & Marius Usher - 2020 - Frontiers in Psychology 11:1069.
    How do people judge the degree of causal responsibility that an agent has for the outcomes of her actions? We show that a relatively unexplored factor -- the robustness of the causal chain linking the agent’s action and the outcome -- influences judgments of causal responsibility of the agent. In three experiments, we vary robustness by manipulating the number of background circumstances under which the action causes the effect, and find that causal responsibility judgments increase with robustness. In the first (...)
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  • The Oxford Handbook of Causal Reasoning.Michael Waldmann (ed.) - 2017 - Oxford, England: Oxford University Press.
    Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Without our ability to discover and empirically test causal theories, we would not have made progress in various empirical sciences. In the past decades, the important role of causal knowledge has been discovered in many areas of cognitive (...)
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