Predicting optimal solution cost with bidirectional stratified sampling (abstract)

Levi H.S. Lelis, Roni Stern, Ariel Felner, Sandra Zilles, Robert C. Holte

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

Abstract

Optimal planning and heuristic search systems solve state-space search problems by finding a least-cost path from start to goal. As a byproduct of having an optimal path they also determine the optimal solution cost. In this paper we focus on the problem of determining the optimal solution cost for a state-space search problem directly, i.e., without actually finding a solution path of that cost. We present an efficient algorithm, BiSS, based on ideas of bidirectional search and stratified sampling that produces accurate estimates of the optimal solution cost. Our method is guaranteed to return the optimal solution cost in the limit as the sample size goes to infinity.

Original languageEnglish
Title of host publicationProceedings of the 5th Annual Symposium on Combinatorial Search, SoCS 2012
Pages186-187
Number of pages2
StatePublished - 1 Dec 2012
Event5th International Symposium on Combinatorial Search, SoCS 2012 - Niagara Falls, ON, Canada
Duration: 19 Jul 201221 Jul 2012

Publication series

NameProceedings of the 5th Annual Symposium on Combinatorial Search, SoCS 2012

Conference

Conference5th International Symposium on Combinatorial Search, SoCS 2012
Country/TerritoryCanada
CityNiagara Falls, ON
Period19/07/1221/07/12

ASJC Scopus subject areas

  • Computer Networks and Communications

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