 The cornerstone of Salmon’s theory of probabilistic causality is the notion of a causal process, defined as a spatio-temporal continuous entity having the capacity to transmit “information, structure and causal influence” (Salmon 1994b [1998: 253]; see also Salmon 1984: 154–157). Processes are responsible for causal propagation, and provide the links connecting causes to effects. By opting for continuous processes, instead of causal chains conceived as collections of events, Salmon diverged from other theories of probabilistic causality, such as those put forward by Patrick Suppes, Irving John Good and Hans Reichenbach. Salmon was deeply convinced that the notion of a causal process can account for many puzzling cases, which other theories find difficult to handle (see Salmon 1980 [1998]). Furthermore, he regarded causal processes as “the kinds of causal connections Hume sought but was unable to find”, holding that “such connections do not violate Hume’s strictures against mysterious powers” (Salmon 1990b [1998: 71]). In order to characterize causal propagation, or transmission, Salmon borrowed from Reichenbach the concept of mark transmission, and from Bertrand Russell the at-at theory of causal propagation.