Predictions and Bounds of IDA* with Conditional Distributions

Uzi Zahavi, Ariel Felner, Neil Burch, Robert C. Holte

Korf, Ried and Edelkamp (AIJ 2001) introduced a formula to predict the number of nodes IDA* will expand given the static distribution of heuristic values. Their formula proved to be very accurate but it is only accurate under the following limitations: (1) the heuristic must be consistent; (2) the prediction is for a large random sample of start states (or for large thresholds). In this paper we generalize the static distribution to a conditional distribution of heuristic values. We then propose a new formula for predicting the performance of IDA* that works well for inconsistent heuristics and for any set of start states, not just a random sample. We also show how the formula can be enhanced to work well for single start states. Experimental results demonstrate the accuracy of our method in all these situations.

Subjects: 15.7 Search; 15.7 Search

Submitted: May 4, 2008


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