The compressed differential heuristic

Meir Goldenberg, Nathan Sturtevant, Ariel Felner, Jonathan Schaeffer

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

Abstract

The differential heuristic (DH) is an effective memory-based heuristic for explicit state spaces. In this paper we aim to improve its performance and memory usage. We introduce a compression method for DHs which stores only a portion of the original uncompressed DH, while preserving enough information to enable efficient search. Compressed DHs (CDH) can be tuned to fit any size of memory, even smaller than the size of the state space. Experimental results across different domains show that, for a given amount of memory, a CDH significantly outperforms an uncompressed DH.

Original languageEnglish
Title of host publicationProceedings of the 4th Annual Symposium on Combinatorial Search, SoCS 2011
Pages191-192
Number of pages2
StatePublished - 2011
Externally publishedYes
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

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