1 research outputs found
Constructing Belief Networks to Evaluate Plans
This paper examines the problem of constructing belief networks to evaluate
plans produced by an knowledge-based planner. Techniques are presented for
handling various types of complicating plan features. These include plans with
context-dependent consequences, indirect consequences, actions with
preconditions that must be true during the execution of an action,
contingencies, multiple levels of abstraction multiple execution agents with
partially-ordered and temporally overlapping actions, and plans which reference
specific times and time durations.Comment: Appears in Proceedings of the Tenth Conference on Uncertainty in
Artificial Intelligence (UAI1994