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Title: On the Parallelization of Greedy Regression Tables
Author(s): D. Vrakas, I. Refanidis, F. Milcent, I. Vlahavas.
Availability: Click here to download the PDF (Acrobat Reader) file (9 pages).
Appeared in: Proc. 18th Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG '99), pp. 180-189, 1999.
Abstract: This paper presents PGRT, a parallel version of a best first planner based on the Greedy Regression Tables approach. The parallelization method of PGRT distributes the task of extracting applicable actions to a given state among the available processors. Although the number of operators limits the scalability of PGRT, it has proven to be quite efficient for low scale parallelization. A modified Operator Reordering method has been used in order to achieve further increase in the efficiency of the parallel algorithm. We illustrate the speedup of PGRT on a variety of hard logistics problems, adopted from the AIPS-98 planning competition.
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1 O. Hatzi, "Web Service Composition through AI Planning", PhD Thesis, Department of Informatics and Telematics, Harokopeio University, 2009