Abstract

We put forth an analysis of causation. The analysis centers on the notion of a causal model that provides only partial information as to which events occur, but complete information about the dependences between the events. The basic idea is this: an event causes another just in case there is a causal model that is uninformative on both events and in which the first event makes a difference as to the occurrence of the other. We show that our analysis captures more causal scenarios than the other counterfactual accounts to date.