Predicting solution cost with conditional probabilities

Levi Lelis, Roni Stern, Shahab Jabbari Arfaee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

Classical heuristic search algorithms find the solution cost of a problem while finding the path from the start state to a goal state. However, there are applications in which finding the path is not needed. In this paper we propose an algorithm that accurately and efficiently predicts the solution cost of a problem without finding the actual solution. We show empirically that our predictor makes more accurate predictions when compared to the bootstrapped heuristic, which is known to be a very accurate inadmissible heuristic. In addition, we show how our prediction algorithm can be used to enhance heuristic search algorithms. Namely, we use our predictor to calculate a bound for a bounded best-first search algorithm and to tune the w-value of Weighted IDA*. In both cases major search speedups were observed.

Original languageEnglish
Title of host publicationProceedings of the 4th Annual Symposium on Combinatorial Search, SoCS 2011
Pages100-107
Number of pages8
StatePublished - 1 Dec 2011
Event4th International Symposium on Combinatorial Search, SoCS 2011 - Barcelona, Spain
Duration: 15 Jul 201116 Jul 2011

Publication series

NameProceedings of the 4th Annual Symposium on Combinatorial Search, SoCS 2011

Conference

Conference4th International Symposium on Combinatorial Search, SoCS 2011
Country/TerritorySpain
CityBarcelona
Period15/07/1116/07/11

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