DocumentCode :
1713258
Title :
Minimizing the number of actions in parallel planning
Author :
Grandcolas, Stéphane ; Pain-Barre, Cyril
Author_Institution :
CNRS, Domaine Univ. de St.-Jerome, Marseille, France
Volume :
2
fYear :
2010
Firstpage :
189
Lastpage :
196
Abstract :
In the domain of classical planning one distinguishes plans which are optimal in their number of actions, they are referred as sequential plans, from plans which are optimal in their number of levels, they are referred as parallel plans. Searching optimal sequential plans is generally considered harder than searching optimal parallel plans. Buttner and Rintanen have proposed a search procedure which computes plans whose numbers of levels are fixed and whose numbers of actions are minimal. This procedure is notably used to calculate optimal sequential plans, starting from an optimal parallel plan. In this paper we describe a similar approach, which we have developed from the planner FDP. The idea consists in maintaining two structures, the first one representing the parallel plan and the other representing the sequential plan, performing the choices simultaneously in both structures. The techniques which were developed in FDP to compute sequential plans or parallel plans enable failures detection in the two structures. Experimental results show that this approach is in some cases more efficient than FDP when searching optimal sequential plans.
Keywords :
parallel processing; planning (artificial intelligence); failures detection; optimal parallel plans; optimal sequential plans; parallel planning; planner FDP; Artificial intelligence; Context; Planning; Random access memory; Search problems; Semantics; optimal parallel planning; optimal sequential planning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2010 22nd IEEE International Conference on
Conference_Location :
Arras
ISSN :
1082-3409
Print_ISBN :
978-1-4244-8817-9
Type :
conf
DOI :
10.1109/ICTAI.2010.100
Filename :
5671414
Link To Document :
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