Scheduling with partial orders and a causal model

In an ongoing project at Honeywell SRC, we are constructing a prototype scheduling system for a NASA domain using the 'Time Map Manager' (TMM). The TMM representations are flexible enough to permit the representation of precedence constraints, metric constraints between activities, and constraints relative to a variety of references (e.g., Mission Elapsed Time vs. Mission Day). The TMM also supports a simple form of causal reasoning (projection), dynamic database updates, and monitoring specified database properties as changes occur over time. The greatest apparent advantage to using the TMM is the flexibility added to the scheduling process: schedules are constructed by a process of 'iterative refinement,' in which scheduling decisions correspond to constraining an activity either with respect to another activity or with respect to one time line. The schedule becomes more detailed as activities and constraints are added. Undoing a scheduling decision means removing a constraint, not removing an activity from a specified place on the time line. For example, we can move an activity around on the time line by deleting constraints and adding new ones

Managing Disjunction for Practical Temporal Reasoning

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 inf..