Applications of data mining to sub-plan selection in automated planning systems

This paper presents a model of the automated planning problem that can extend the range of tractable problems, and decrease the solution time for already tractable ones. It uses the concept of midpoint navigation to reduce planning problems with solutions of length N, into sub-problems with reduced length. Due to the exponential elaboration time of planning problems, this provides significant benefit to the planner. However, a critical aspect of this approach is selecting ´good´ midpoints for evaluation. We argue that several established data mining techniques might be used to determine these waypoints, and outline methods for applying these techniques