AAAI Publications, Tenth Annual Symposium on Combinatorial Search

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Improving a Planner’s Performance through Online Heuristic Configuration of Domain Models
Mauro Vallati, Lukás Chrpa, Thomas Leo McCluskey

Last modified: 2017-06-06

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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