Predicting the performance of IDA* with conditional distributions Conference Paper uri icon


  • Abstract (Korf, Reid, and Edelkamp 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 con-sistent;(2) the prediction is for a large random sample of start states. In this paper we generalize the static dis-tribution to a conditional distribution of heuristic val-ues. We then propose a new formula for predicting the performance of IDA* that works well for inconsistent heuristics (Zahavi et al. 2007) 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.

publication date

  • January 1, 2008