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. Hence, ranking theory with its resources of formalizing defeasible reasoning or inductive schemes seems ideally suited to explicate the idea 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)

In this paper two theories of defeasible reasoning, Pollock's account and my theory of ranking functions, are compared, on a strategic level, since a strictly formal comparison would have been unfeasible. A brief summary of the accounts shows their basic difference: Pollock's is a strictly computational one, whereas ranking functions provide a regulative theory. Consequently, I argue that Pollock's theory is normatively defective, unable to provide a theoretical justification for its basic inference rules and thus an independent notion of admissible (...) rules. Conversely, I explain how quite a number of achievements of Pollock's account can be adequately duplicated within ranking theory. The main purpose of the paper, though, is not to settle a dispute with formal epistemology, but rather to emphasize the importance of formal methods to the whole of epistemology. (shrink)

The key idea of the interventionist account of causation is that a variable A causes a variable B if and only if B would change if A were manipulated in the appropriate way. This paper raises two problems for Woodward's (2003) version of interventionism. The first is that the conditions it imposes are not sufficient for causation, because these conditions are also satisfied by non-causal relations of nomological dependence expressed in association laws. Such laws ground a relation of mutual manipulability (...) that is incompatible with the asymmetry of causation. Several ways of defending the interventionist account are examined and found unsatisfying. The second problem is that it often seems to be impossible, in a model that contains variables linked by an association law, to satisfy the conditions imposed on interventions on such variables. Various ways to solve this second problem, most importantly the analysis of manipulability in terms of difference making, are examined. Given that none solves the problem, I conclude that the interventionist conditions are neither sufficient nor necessary for causation. It is suggested that they provide an analysis of nomological dependence, which may be supplemented with the notion of a causal process to yield an analysis of causation. (shrink)

The paper displays the similarity between the theory of probabilistic causation developed by Glymour et al. since 1983 and mine developed since 1976: the core of both is that causal graphs are Bayesian nets. The similarity extends to the treatment of actions or interventions in the two theories. But there is also a crucial difference. Glymour et al. take causal dependencies as primitive and argue them to behave like Bayesian nets under wide circumstances. By contrast, I argue the behavior of (...) Bayesian nets to be ultimately the defining characteristic of causal dependence. (shrink)