Questions and answers about philosophy of science, causation, and human/machine learning
نویسنده
چکیده
(A) Explain how the tools of statistical learning (Bayesian or otherwise) might be useful in thinking about paradigm shifts in science. Is a paradigm shift just the replacement of one model or hypothesis by another, or does it involve something more? (B) What would be the analogy of a Kuhnian paradigm shift in human learning or machine learning? Give at least one specific example of a phenomenon of human learning, and also a phenomenon from machine learning, that can be thought of productively in terms of paradigm shifts.
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