 There is a third approach to the problem of idealization: to some Bayesians, some aspects of the Bayesian idealization are to be utilized rather than removed, because it is those aspects of idealization that empower certain important applications of Bayesian epistemology in science. Here is the idea. Consider a human scientist confronted with an empirical problem. When some hypotheses have been stated for consideration and some data have been collected, there remains an inferential task—the task of inferring from the data to one of the hypotheses. This inferential task can be done by human scientists alone, but it has been done increasingly often this way: by developing a computer program (in Bayesian statistics) to simulate an idealized Bayesian agent as if that agent were hired to perform the inferential task. The purpose of this inferential task would be undermined if what is simulated by the computer were a cognitively underpowered agent who mimics the limited capacities of human agents. Howson (1992: sec. 6) suggests that this inferential task is what Bayesian epistemology and Bayesian statistics were mainly designed for at the early stages of their development. See Fienberg (2006) for the historical development of Bayesian statistics.