In Proceedings of the International Joint Conference on Artificial Intelligence, pages 1606-1611, 1995.
The use of primary effects in planning is an effective approach to reducing search. The underlying idea of this approach is to select certain "important" effects among the effects of each operator and to use an operator only for achieving its important effects. In the past, there has been little analysis of planning with primary effects and few experimental results. We provide empirical and analytical results on the use of primary effects. First, we experimentally demonstrate that the use of primary effects may lead to an exponential reduction of the planning time. Second, we analytically explain the experimental results and identify the factors that influence the efficiency of planning with primary effects. Third, we describe an application of our analysis to predicting the performance of a planner for a given selection of primary effects.