Description

As we develop larger and more complex intelligent systems in knowledge-intensive domains, it becomes impractical to develop knowledge bases from scratch. Recent research investigates how to develop intelligent systems by drawing from libraries of reusable components that include both ontologies and problem-solving methods. Planet is a reusable ontology for representing plans that is designed to accomodate a diverse range of real-world plans, both manually and automatically created. We have drawn from our past experience in designing, developing and integrating planning tools, and expect planet to ease these tasks in the future in three ways. First, we have already found it useful for knowledge modelling. By providing a structure that formalizes useful distinctions for reasoning about states and actions, a knowledge engineer can find the semantics of informal expressions of plans (e.g., textual or domain-specific) through designing mappings to the ontology. Second, a plan ontology can be a central vehicle for knowledge reuse across planning applications. Planet contains general, domain-independent definitions that are common and useful across planning domains. Third, Planet can facilitate integration of planning tools through knowledge sharing.

Currently, practical efforts to integrate planning tools are done by designing separate interchange formats for (almost) each pair of tools, since designing a more universal format is costly and often more difficult than designing the entire set of pairwise formats. These difficulties are in part because these systems include decision-support tools such as plan editors, plan evaluation tools, and plan critiquers, which represent plans in ways that are different from traditional AI plan generation systems. Planet can provide a shared plan representation for systems to communicate and exhange information about the plan, and can facilitate the creation of a common, overarching knowledge base for future integrations of planning tools.

Planet is available in Loom, KIF, and CycL. Send email to Jim Blythe (blythe@isi.edu) or Yolanda Gil (gil@isi.edu) if you would be interested in seeing the latest version.

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