Plan synthesis: a logical perspective
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 1
Planning under uncertainty and its applications
Reasoning, Action and Interaction in AI Theories and Systems
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Problem solving with incomplete information is usually very costly, since multiple alternatives must be taken into account in the planning process. In this paper, we present some pruning rules that lead to substantial cost savings. The rules are all based on the simple idea that, if goal achievement is the sole criterion for performance, a planner need not consider one "branch" in its search space when there is another "branch" characterized by equal or greater information. The idea is worked out for the cases of sequential planning, conditional planning, and interleaved planning and execution. The rules are of special value in this last case, as they provide a way for the problem solver to terminate its search without planning all the way to the goal and yet be assured that no important alternatives are overlooked.