Vallati, Mauro, Chrpa, Lukáš and McCluskey, T.L. (2017) Improving a planner’s performance through online heuristic configuration of domain models. In: Proceedings of the 10th International Symposium on Combinatorial Search (SoCS). AAAI Press, pp. 171-172. ISBN 978-1577357902
Abstract

The separation of planner logic from domain knowledge supports the use of reformulation and configuration techniques, such as macro-actions and entanglements, which transform the model representation in order to improve a planner’s performance. One drawback of such an approach is that it may require a potentially expensive training phase.
In this paper, we introduce heuristic approaches for the online configuration of planning domain models. The proposed
heuristics consider different aspects of PDDL-encoded operators for reordering such operators in the domain model, relying on the assumption that the way in which operators are encoded carries useful information about their expected use

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