Using available memory to transform Graphplan's search

Terry Zimmerman, Subbarao Kambhampati

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a major variant of the Graphplan algorithm that employs available memory to transform the depth-first nature of Graphplan's search into an iterative state space view in which heuristics can be used to traverse the search space. When the planner, PEGG, is set to conduct exhaustive search, it produces guaranteed optimal parallel plans 2 to 90 times faster than a version of Graph-plan enhanced with CSP speedup methods. By heuristically pruning this search space PEGG produces plans comparable to Graphplan's in make-span, at speeds approaching state-of-the-art heuristic serial planners.

Original languageEnglish (US)
Title of host publicationIJCAI International Joint Conference on Artificial Intelligence
Pages1526-1527
Number of pages2
StatePublished - 2003
Event18th International Joint Conference on Artificial Intelligence, IJCAI 2003 - Acapulco, Mexico
Duration: Aug 9 2003Aug 15 2003

Other

Other18th International Joint Conference on Artificial Intelligence, IJCAI 2003
CountryMexico
CityAcapulco
Period8/9/038/15/03

ASJC Scopus subject areas

  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Using available memory to transform Graphplan's search'. Together they form a unique fingerprint.

  • Cite this

    Zimmerman, T., & Kambhampati, S. (2003). Using available memory to transform Graphplan's search. In IJCAI International Joint Conference on Artificial Intelligence (pp. 1526-1527)