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The value of rational analysis: An assessment of causal reasoning and learning

In Nick Chater & Mike Oaksford (eds.), The Probabilistic Mind: Prospects for Bayesian Cognitive Science. Oxford University Press. pp. 486--500 (2008)

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  1. Comments on Quantum Probability Theory.Steven Sloman - 2014 - Topics in Cognitive Science 6 (1):47-52.
    Quantum probability theory (QP) is the best formal representation available of the most common form of judgment involving attribute comparison (inside judgment). People are capable, however, of judgments that involve proportions over sets of instances (outside judgment). Here, the theory does not do so well. I discuss the theory both in terms of descriptive adequacy and normative appropriateness.
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  • Getting counterfactuals right: the perspective of the causal reasoner.Elena Popa - 2022 - Synthese 200 (1):1-18.
    This paper aims to bridge philosophical and psychological research on causation, counterfactual thought, and the problem of backtracking. Counterfactual approaches to causation such as that by Lewis have ruled out backtracking, while on prominent models of causal inference interventionist counterfactuals do not backtrack. However, on various formal models, certain backtracking counterfactuals end up being true, and psychological evidence shows that people do sometimes backtrack when answering counterfactual questions in causal contexts. On the basis of psychological research, I argue that while (...)
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  • Téléologie et fonctions en biologie. Une approche non causale des explications téléofonctionnelles.Alberto Molina Pérez - 2017 - Dissertation, Universidad Autónoma de Madrid
    This dissertation focuses on teleology and functions in biology. More precisely, it focuses on the scientific legitimacy of teleofunctional attributions and explanations in biology. It belongs to a multi-faceted debate that can be traced back to at least the 1970s. One aspect of the debate concerns the naturalization of functions. Most authors try to reduce, translate or explain functions and teleology in terms of efficient causes so that they find their place in the framework of the natural sciences. Our approach (...)
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  • How could a rational analysis model explain?Samuli Reijula - 2017 - COGSCI 2017: 39th Annual Conference of the Cognitive Science Society,.
    Rational analysis is an influential but contested account of how probabilistic modeling can be used to construct non-mechanistic but self-standing explanatory models of the mind. In this paper, I disentangle and assess several possible explanatory contributions which could be attributed to rational analysis. Although existing models suffer from evidential problems that question their explanatory power, I argue that rational analysis modeling can complement mechanistic theorizing by providing models of environmental affordances.
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