 Reichenbach’s eventual anti-foundationalism led him to a contest of opinions with C.I. Lewis, whose accounts of empirical learning and reasoning in Mind and the World Order (1929), and in An Analysis of Knowledge and Valuation (1946) rested on a phenomenalist foundation of “qualia” (see the entry on  qualia).  Lewis, like Reichenbach a probabilist at heart, insisted that the assessment and revision of probabilities in the light of experience requires that some propositions obtained from experience be certain, or as he put it, “if anything is probable, something must be certain.” Reichenbach denied the claim, arguing that the deliverances of experience directly provide, not certainty for claims about qualia, but only probabilities for claims about ordinary things. Those probabilities can be revised in the light of further experience. For the same reason, in his unremittingly critical review of Karl Popper’s The Logic of Scientific Discovery (Popper 1935), Reichenbach argues that probability assessments are essential in the “falsification” of theories (1935e, 1978, vol. 2, p. 372). Lewis’ actual complaint appears to be based on a mathematical error when computing conditional probabilities. Reichenbach pointed out Lewis’ error, but did not provide a positive example to refute Lewis’ concern (Peijnenburg &amp; Atkinson, 2011). A more general problem that appears to have been missed in the discussion at the time is that since Reichenbach held that the probabilities of theories are to be assessed by Bayes rule, his position, unlike Lewis’, required a technical account of how claims with non-extremal probabilities can produce changes in the probabilities of others by some generalization of Bayes rule (see the entry on  Bayes Theorem).  Since on Reichenbach’s view uncertainty is associated with observation and perception and scientific theories are only confirmed with a degree of probability, an account is required of how uncertain data changes the probabilities of hypotheses logically remote from the data. Much later, Richard Jeffrey (1983) provided an account of Bayesian updating that explicitly relates the probability of the data to the probability of the hypothesis confirmed—or disconfirmed—by the data (see the entry on  Bayesian epistemology).  