Faster bounded-cost search using inadmissible estimates

Jordan T. Thayer, Roni Stern, Ariel Felner, Wheeler Ruml

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

28 Scopus citations

Abstract

Many important problems are too difficult to solve optimally. A traditional approach to such problems is bounded suboptimal search, which guarantees solution costs within a user-specified factor of optimal. Recently, a complementary approach has been proposed: bounded-cost search, where solution cost is required to be below a user-specified absolute bound. In this paper, we show how bounded-cost search can incorporate inadmissible estimates of solution cost and solution length. This information has previously been shown to improve bounded suboptimal search and, in an empirical evaluation over five benchmark domains, we find that our new algorithms surpass the state-of-the-art in bounded-cost search as well, particularly for domains where action costs differ.

Original languageEnglish
Title of host publicationICAPS 2012 - Proceedings of the 22nd International Conference on Automated Planning and Scheduling
Pages270-278
Number of pages9
StatePublished - 25 Sep 2012
Event22nd International Conference on Automated Planning and Scheduling, ICAPS 2012 - Atibaia, Sao Paulo, Brazil
Duration: 25 Jun 201229 Jun 2012

Publication series

NameICAPS 2012 - Proceedings of the 22nd International Conference on Automated Planning and Scheduling

Conference

Conference22nd International Conference on Automated Planning and Scheduling, ICAPS 2012
Country/TerritoryBrazil
CityAtibaia, Sao Paulo
Period25/06/1229/06/12

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