PLANET
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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 ntegrating 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 should 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. An ontology like 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. We use Planet in our work on a problem-solving method for plan evaluation. There is more information in the following article:
Contact: Jim Blythe |