In order to perform adequately in real-world situations, a planning system must be able to nd the \best" solution while still supporting anytime behavior. We have developed a method for incrementally optimizing plans called iterative strengthening that can be used in many situations where other optimization methods are not appropriate. In particular, iterative strengthening supports optimized planning within an \anytime" environment using multiple simultaneous optimizing parameters, and it can be adapted to support inadmissible heuristics and undecidable domains.
Randall J. Calistri-Yeh