 Much of John McCarthy’s early work in artificial intelligence concerned the interpretation of stories and puzzles (McCarthy and Hayes 1969; McCarthy 1977). McCarthy found that we often make assumptions based on what is not said. So, for example, in a puzzle about safely crossing a river by canoe, we assume that there are no bridges or other means of conveyance available. Similarly, when using a database to store and convey information, the information that, for example, no flight is scheduled at a certain time is represented simply by not listing such a flight. Inferences based on these conventions are defeasible, however, because the conventions can themselves be explicitly abrogated or suspended.