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Problem Splitting Using Heuristic Search in Landmark Orderings
TLDR
We lay in this paper the foundations of a meta best-first search algorithm, which explores the landmark orderings to create subproblems and can use any embedded planner to solve them. Expand
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The virtual lands of Oz: testing an agribot in simulation
TLDR
Testing autonomous robots typically requires expensive test campaigns in the field. Expand
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Parallel AI Planning on the SCC
We present in this paper a parallelized version of an existing Artificial Intelligence automated planner, implemented with standard programming models and tools (hybrid OpenMP/MPI). We then evaluateExpand
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Landmark-based Meta Best-First Search Algorithm : First Parallelization Attempt and Evaluation
In this paper, we revisit the idea of splitting a planning problem into subproblems hopefully easier to solve with the help of landmark analysis. While this technique initially proposed in the firstExpand
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The Landmark-based Meta Best-First Search Algorithm for Classical Planning
TLDR
In this paper, we revisit the idea of splitting a planning problem into subproblems hopefully easier to solve with the help of landmark analysis. Expand
Décomposition des problèmes de planification de tâches basée sur les landmarks
Les algorithmes permettant la creation de strategies efficaces pour la resolution d’ensemble de problemesheteroclites ont toujours ete un des piliers de la recherche en Intelligence Artificielle.Expand
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