Abstraction-based heuristics with true distance computations

Ariel Felner, Nathan Sturtevant, Jonathan Schaeffer

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

17 Scopus citations

Abstract

Pattern Databases (FDBs) are the most common form of memory-based heuristics, and they have been widely used in a variety of permutation puzzles and other domains. We explore the (rue-distance heuristics (TDHs) (also appeared in (Sturtevant et al 2009)) which are a different form of memory-based heuristics, designed to work in problem states where there isn't a fixed goal state. Unlike PDBs, which build a heuristic based on distances in an abstract state space, TDHs store distances which are computed in the actual state space. We look in detail at how TDHs work, providing both theoretical and experimental motivation for their use.

Original languageEnglish
Title of host publicationSARA 2009 - Proceedings, 8th Symposium on Abstraction, Reformulation and Approximation
Pages74-81
Number of pages8
StatePublished - 1 Dec 2009
Event8th Symposium on Abstraction, Reformulation and Approximation, SARA 2009 - Lake Arrowhead, CA, United States
Duration: 7 Jul 200910 Jul 2009

Publication series

NameSARA 2009 - Proceedings, 8th Symposium on Abstraction, Reformulation and Approximation

Conference

Conference8th Symposium on Abstraction, Reformulation and Approximation, SARA 2009
Country/TerritoryUnited States
CityLake Arrowhead, CA
Period7/07/0910/07/09

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