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Article type: Research Article
Authors: Cooper, Martin C. | de Roquemaurel, Marie | Régnier, Pierre
Affiliations: IRIT, University of Toulouse III, Toulouse, France. E-mails: {cooper, deroquemaurel, regnier}@irit.fr
Note: [] Corresponding author: Martin C. Cooper, IRIT, University of Toulouse III, 118 route de Narbonne, 31062 Toulouse, France. E-mail: cooper@irit.fr.
Abstract: For planning to come of age, plans must be judged by a measure of quality, such as the total cost of actions. This paper describes an optimal-cost planner which guarantees global optimality whenever the planning problem has a solution. We code the extraction of an optimal plan, from a planning graph with a fixed number k of levels, as a weighted constraint satisfaction problem (WCSP). The specific structure of the resulting WCSP means that a state-of-the-art exhaustive solver was able to find an optimal plan in planning graphs containing several thousand nodes. Thorough experimental investigations demonstrated that using the planning graph in optimal planning is a practical possibility for problems of moderate size, although not competitive, in terms of computation time, with optimal state-space-search planners. Our general conclusion is, therefore, that planning-graph-based optimal planning is not the most efficient method for cost-optimal planning. Nonetheless, the notions of indispensable (sets of) actions and too-costly actions introduced in this paper have various potential applications in optimal planning. These actions can be detected very rapidly by analysis of the relaxed planning graph.
Keywords: Optimal planning, planning graph, soft constraints, soft arc consistency
DOI: 10.3233/AIC-2010-0473
Journal: AI Communications, vol. 24, no. 1, pp. 1-29, 2011
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