Reasons as causes in Bayesian epistemology

Journal of Philosophy

Volumn 104, Issue 9, 2007, Pages 464-474

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EID: 60950231698     PISSN: 0022362X     EISSN: 19398549     Source Type: Journal    
DOI: 10.5840/jphil200710499     Document Type: Review

References (9)

1. Aaron P. Blaisdell, Kosuke Sawa, Kenneth J. Leising, and Michael R.Waldmann, "Causal Reasoning in Rats, " Science, CCCXI (2006): 1020-22.
2. For example, Karl Pearson, The Grammar of Science (Mineola, NY: Dover, 2004). Originally published in 1892 and still in print, Pearson maintains thatcausation is correlation and that there is no fact to the matter of correlationor causation because what we experience is events in our brains.
3. Alison Gopnik, Glymour, David M. Sobel, Laura E. Schulz, Tamar Kushnir, and David Danks, "A Theory of Causal Learning in Children: Causal Maps and Bayes Nets, " Psychological Review, CXI (2004): 3-32;
4. Gopnik and Schulz, eds., Causal Learning: Psychology, Philosophy, and Computation (New York: Oxford, 2007);
5. Steven A. Sloman, Causal Models: How People Think about the World and Its Alternatives (New York: Oxford, 2005).
6. Algorithms for computing the effects of interventions that fix a definitevalue for one or more variables are given in Judea Pearl, Causality: Models, Reasoning, and Inference (New York: Cambridge, 2000),
7. and discussed as a foundation for understanding causation by James Woodward, Making Things Happen: A Theory of Causal Explanation (New York:Oxford, 2003).
8. Rajesh R.N. Rao, "Bayesian Inference and Attentional Modulation inthe Visual Cortex, " Cognitive Neuroscience and Neuropsychology, XVI (2005):1843-48.
9. See also: Kenji Doya, Shin Ishii, Alexandre Pouget, and Rao, eds., Bayesian Brain: Probabilistic Approaches to Neural Coding (Cambridge: MIT, 2007).