Predictions and bounds of IDA* with conditional distributions

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

Research output: Contribution to conferencePaperpeer-review


(Korf, Reid, & 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 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 (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.

Original languageEnglish
Number of pages7
StatePublished - 1 Dec 2008
Event2008 AAAI Workshop - Chicago, IL, United States
Duration: 13 Jul 200813 Jul 2008


Conference2008 AAAI Workshop
Country/TerritoryUnited States
CityChicago, IL

ASJC Scopus subject areas

  • Engineering (all)

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