Probably approximately correct heuristic search

Roni Stern, Ariel Felner, Robert Holte

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

3 Scopus citations

Abstract

A* is a best-first search algorithm that returns an optimal solution. w-admissible algorithms guarantee that the returned solution is no larger than w times the optimal solution. In this paper we introduce a generalization of the w-admissibility concept that we call PAC search, which is inspired by the PAC learning framework in Machine Learning. The task of a PAC search algorithm is to find a solution that is w-admissible with high probability. In this paper we formally define PAC search, and present a framework for PAC search algorithms that can work on top of any search algorithm that produces a sequence of solutions. Experimental results on the 15-puzzle demonstrate that our framework activated on top of Anytime Weighted A* (AWA*) expands significantly less nodes than regular AWA* while returning solutions that have almost the same quality.

Original languageEnglish
Title of host publicationProceedings of the 4th Annual Symposium on Combinatorial Search, SoCS 2011
Pages158-163
Number of pages6
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

ASJC Scopus subject areas

  • Computer Networks and Communications

Fingerprint

Dive into the research topics of 'Probably approximately correct heuristic search'. Together they form a unique fingerprint.

Cite this