 A number of authors have attempted to provide probabilistic analyses of actual causation. Some, such as Eells (1991: chapter 6), Kvart (1997, 2004), and Glynn (2011), pay careful attention to the way in which probabilities change over time. Some, such as Dowe (2004) and Schaffer (2001), combine probabilities with the resources of a process theory of causation. Some, such as Lewis (1986b), Menzies (1989), and Noordhof (1999), employ probabilities together with counterfactuals to analyze actual causation. And others such as Beckers &amp; Vennekens (2016), Fenton-Glynn (2017), Halpern (2016: Section 2.5), Hitchcock (2004a), and Twardy &amp; Korb (2011) employ causal modeling tools similar to those described in  Section 3.  We will describe two of those theories—Lewis (1986b) and Fenton-Glynn (2017)—in more detail in sections  4.3  and  4.4  below. 