Improving a planner’s performance through online heuristic configuration of domain models

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)


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.
Original languageEnglish
Title of host publicationProceedings of the Tenth International Symposium on Combinatorial Search (SoCS 2017)
EditorsAlex Fukunaga, Akihiro Kishimoto
PublisherAAAI press
Number of pages2
ISBN (Print)9781577357902, 1577357906
Publication statusPublished - 15 Jun 2017
Event10th Annual Symposium on Combinatorial Search - Pittsburgh, United States
Duration: 16 Jun 201717 Jun 2017
Conference number: 10 (Link to Symposium Website )


Conference10th Annual Symposium on Combinatorial Search
Abbreviated titleSoCS 2017
Country/TerritoryUnited States
Internet address


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