 As the subdiscipline of artificial intelligence took shape in the 1960s, pioneers like John M. McCarthy and Patrick J. Hayes soon discovered the need to represent and implement the sort of defeasible reasoning that had been identified by Aristotle and Chisholm. McCarthy and Hayes (McCarthy and Hayes 1969) developed a formal language they called the “situation calculus,” for use by expert systems attempting to model changes and interactions among a domain of objects and actors. McCarthy and Hayes encountered what they called the frame problem: the problem of deciding which conditions will not change in the wake of an event. They required a defeasible principle of inertia: the presumption that any given condition will not change, unless required to do so by actual events and dynamic laws. In addition, they encountered the qualification problem: the need for a presumption that an action can be successfully performed, once a short list of essential prerequisites have been met. McCarthy (McCarthy 1977, 1038–1044) suggested that the solution lay in a logical principle of circumscription: the presumption that the actual situation is as unencumbered with abnormalities and oddities (including unexplained changes and unexpected interferences) as is consistent with our knowledge of it. (McCarthy 1982; McCarthy 1986) In effect, McCarthy suggests that it is warranted to believe whatever is true in all the minimal (or otherwise preferred) models of one’s initial information set.