I don't think that is how CDT and EDT differ, actually. Instead, it's that EDT cares about conditional probabilities and CDT doesn't. For instance, in Newcomb's problem, a CDT agent could agree that his expected utility is higher conditional on him one-boxing than it is conditional on him two-boxing. But he two-boxes anyway because the correlation isn't causal. A guess TDT/UDT does compute conditional probabilities differently in the sense that they don't pretend that their decisions are independent of the outputs of similar algorithms.