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Title:Branching and Pruning: An Optimal Temporal POCL Planner based on Constraint Programming
Authors: V Vidal ; Hector Geffner
Date:Mar 2006
Publication Title:Artifical Intelligence
Publication Type:Journal Article
Volume No:170 (3) Page Nos:298-335
DOI:10.1016/j.artint.2005.08.004 ISBN/ISSN:0004-3702
A key feature of modern optimal planners such as Graphplan and Blackbox is their ability to prune large parts of the search space. Previous Partial Order Causal Link (POCL) planners provide an alternative branching scheme but lacking comparable pruning mechanisms do not perform as well. In this paper, a domain-independent formulation of temporal planning based on Constraint Programming is introduced that successfully combines a POCL branching scheme with powerful and sound pruning rules. The key novelty in the formulation is the ability to reason about supports, precedences, and causal links involving actions that are not in the plan. Experiments over a wide range of benchmarks show that the resulting optimal temporal planner is much faster than current ones and is competitive with the best parallel planners in the special case in which actions have all the same duration.
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Bibtex format
author = { V Vidal and Hector Geffner },
title = {Branching and Pruning: An Optimal Temporal POCL Planner based on Constraint Programming},
journal = {Artifical Intelligence},
publisher = {Elsevier},
year = 2006,
month = {Mar},
volume = {170 (3)},
pages = {298-335},
doi = {10.1016/j.artint.2005.08.004},
url = {},

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