Abstract
Ambiguous conclusions are inescapable in temporal reasoning. Lack of precise information about what events happen when results in uncertainty regarding the events’ effects. Incomplete information and nonmonotonic inference result in situations where there is more than one set of possible conclusions, even when there is no temporal uncertainty at all. In an implemented system, this ambiguity is a computational problem as well as a semantic one. We discuss some of the sources of this ambiguity, which we treat as explicit disjunction, in the sense that ambiguous information can be interpreted as defining a set of possible inferences. Three ways of handling this disjunction are to represent it explicitly, to remove it by limiting the expressive power of the system, or to approximate a set of disjuncts using a weaker form of representation. We have employed primarily the latter two of these approaches to implement an expressive and efficient temporal reasoning engine that performs sound inference in accordance with a well-defined formal semantics.