Normic Laws and the Significance of Nonmonotonic Reasoning for Philosophy of Science. Normic laws have the form ‘if A then normally B’. They have been discovered in the explanation debate, but were considered as empirically vacuous (§1). I argue that the prototypical (or ideal) normality of normic laws implies statistical normality (§2), whence normic laws have empirical content. In §3–4 I explain why reasoning from normic laws is nonmonotonic, and why the understanding of the individual case is so important here. (...) After sketching some foundations of nonmonotonic reasoning as developed by AI-researchers (§5), Iargue that normic laws are also the best way to understand ceteris paribus laws (§6). §7 deals with the difference between physical and non-physical disciplines and §9 with the difference between normicity and approximation. In §8 it is shown how nonmonotonic reasoning provides a new understanding of the protection of theories against falsification by auxiliary hypotheses. §10, finally, gives a system- and evolution-theoretical explanation of the deeper reason for the omnipresence of normic laws in practice and science, and forthe connection between ideal and statistical normality. (shrink)

The characteristic difference between laws and accidental generalizations lies in our epistemic or inductive attitude towards them. This idea has taken various forms and dominated the discussion about lawlikeness in the last decades. Likewise, the issue about ceteris paribus conditions is essentially about how we epistemically deal with exceptions. Hence, ranking theory with its resources of defeasible reasoning seems ideally suited to explicate these points in a formal way. This is what the paper attempts to do. Thus it will turn (...) out that a law is simply the deterministic analogue of a sequence of independent, identically distributed random variables. This entails that de Finetti's representation theorems can be directly transformed into an account of confirmation of laws thus conceived. (shrink)

Dogmatic, naive and sophisticated falsificationism are construed as being distinguished by different views on the revisability of scientific theories. Then Lakatos's methodology of scientific research programs (SRP) is reinterpreted: The structure of an SRP is a target theory equipped with a priority structure for hypothetical revisions that accommodate idealizing assumptions. Idealizations pointing "backwards" capture predecessor theories, thus showing both their virtues and limitations. The core of an SRP is assigned top priority; its positive heuristics consists in a strategy of how (...) to work off the idealizing assumptions. In the dynamics of SRP's, progressive intertheoretic relations within an SRP are characterized as generating continuity through revisions, while those that hold across SRP's only have excess empirical content. Finally, we contrast our account with a reconstruction of Lakatos's in the structuralist philosophy of science (W. Stegmüller). (shrink)

Drawing inspiration from Lakatos’s philosophy of science, the paper presents a notion of intertheory explanation that is suitable to explain, from the point of view of a successor theory, its predecessor theory’s success (where it is successful) as well as the latter’s failure (where it fails) at the same time. A variation of the Ramsey-test is used, together with a standard AGM belief revision model, to give a semantics for open and counterfactual conditionals and ’because’-sentences featuring in such intertheory explanations. (...) Pre-theoretically described idealizing assumptions play a crucial role in this model, especially when the predecessor theory and the successor theory contradict each other. (shrink)