No abstract

No abstract

Recent work in psychology and experimental philosophy has shown that judgments of actual causation are often influenced by consideration of defaults, typicality, and normality. A number of philosophers and computer scientists have also suggested that an appeal to such factors can help deal with problems facing existing accounts of actual causation. This paper develops a flexible formal framework for incorporating defaults, typicality, and normality into an account of actual causation. The resulting account takes actual causation to be both graded and comparative. We then show how our account would handle a number of standard cases. * For helpful comments and discussion, we would like to thank

No abstract

When a scientist uses an observation to formulate a theory, it is no surprise that the resulting theory accurately captures that observation. However, when the theory makes a novel predictionÐwhen it predicts an observation that was not used in its formula-tionÐthis seems to provide more substantial con®rmation of the theory. This paper presents a new approach to the vexed problem of understanding the epistemic difference between prediction and accommodation. In fact, there are several problems that need to be disentangled; in all of them, the key is the concept of over®tting. We¯oat the hypothesis that accommodation is a defective methodology only when the methods used to accommodate the data fail to guard against the risk of over®tting. We connect our analysis with the proposals that other philosophers have made. We also discuss its bearing on the con¯ict between instrumentalism and scienti®c realism. 1 Introduction 2 PredictivismsÐa taxonomy 3 Observations 4 Formulating the problem 5 What might Annie be doing wrong? 6 Solutions 7 Observations explained 8 Mayo on severe tests 9 The miracle argument and scientific realism 10 Concluding comments