Temporal reasoning, which is a way of pursuing goals and drawing inferences based on events occurring over time, plays an important role in automated planning systems and in general in common sense reasoning. This work is an attempt at exploring the problems involved in reasoning over time which typically involve updating a plan structure with changing world patterns. This involves developing the appropriate knowledge representation in addition to a plan generation system. A deductive retrieval mechanism, which has been tailored to the needs of temporal retrievals, has been imple-mented. Uncertainty due to incomplete information and indecision is resolved using fuzzy values and a dynamic resolution over a temporal data base. Imprecise temporal information is captured in fuzzy intervals. These intervals are made up of a beginning hour and ending hour. The system can find the tightest possible bounds on a possible event or step in a plan. The system user provides the constraint information for plan development. This is combined with basic domain information in the knowledge base. A plan or set of steps through some temporal constraints will be presented based upon the constraints and domain information. A fuzzy belief in the chance of the plans' success is associated with the information provided by the system.
Bharadwaj S. Tirumala,
Lawrence O. Hall,
"A System For Temporal Plan Generation", Proc. SPIE 1095, Applications of Artificial Intelligence VII, (21 March 1989); doi: 10.1117/12.969348; https://doi.org/10.1117/12.969348