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Ontologies are known for their ability to organize rich metadata, support theidentification of novel insights via semantic queries, and promote reuse. Inthis paper, we consider the problem of automated planning, where the objectiveis to find a sequence of actions that will move an agent from an initial stateof the world to a desired goal state. We hypothesize that given a large numberof available planners and diverse planning domains; they carry essentialinformation that can be leveraged to identify suitable planners and improvetheir performance for a domain. We use data on planning domains and plannersfrom the International Planning Competition (IPC) to construct a planningontology and demonstrate via experiments in two use cases that the ontology canlead to the selection of promising planners and improving their performanceusing macros - a form of action ordering constraints extracted from planningontology. We also make the planning ontology and associated resources availableto the community to promote further research.

A Planning Ontology to Represent and Exploit Planning Knowledge for Performance Efficiency