Hierarchical Bayesian models as formal models of causal reasoning

@article{Hagmayer2013HierarchicalBM,
  title={Hierarchical Bayesian models as formal models of causal reasoning},
  author={York Hagmayer and Ralf Mayrhofer},
  journal={Argument & Computation},
  year={2013},
  volume={4},
  pages={36-45}
}
knowledge can come in various forms, and it may form complex hierarchies. The most abstract form of knowledge may be called causal principles, which probably include the assumption that causes precede their effects, that nothing happens without a cause, and that causes generate their effect unless prevented by an inhibitory factor (Audi 1995). A fundamental assumption might also be that a manipulation of a cause changes its effects but not vice versa (Woodward 2003). People seem to… CONTINUE READING
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