To download Winzip software to decompress the file click here . To download Ghostscript software to view or print the decompressed postscript file click here . I aim to provide practical answers to these two questions of a sort that is of use to those in the field of Artificial Intelligence who need to program computers to do diagnosis, as well as to those with a general interest in the logic of reasoning.
Diagnosis is a type of reasoning to the causes of some given symptoms.
Consequently any normative model of diagnosis must rely on some account of reasoning and some account of causation. I look at reasoning first and develop a model of rational belief based on the subjective interpretation of probability, though I introduce a more general normative framework and argue for other rational norms in combination with the probabilistic norm. Then I turn to causation, first rebutting scepticism about causation, and then briefly discussing current philosophical views on causation. I claim that no one view on its own can account for all our intuitions on causation. Instead I develop an implicit definition account of causation, whereby probabilistic predictions can be derived from a causal theory, and the theory confirmed according to the accuracy of those predictions.