shaken-3.0
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http://www.ai.sri.com/project/SHAKEN
shaken-3.0
The High Performance Knowledge Bases (HPKB) project demonstrated that the teams of knowledge engineers working together could create
knowledge bases (KBs) roughly at the rate of 10K axioms/year for a pre-specified task and evaluation criteria.
The HPKB effort
showed that it is possible to create KBs by reusing the content of knowledge libraries, and it demonstrated reuse rates ranging from
25% to 100%, depending on the application and the knowledge engineer.
It was acknowledged that the ability of a subject matter
expert (SME) to directly enter knowledge is essential to improve the KB construction rates.
The goal of the Rapid Knowledge
Formation (RKF) project is to explore and create innovative techniques for SMEs to directly enter knowledge.
The SRI team is developing a system for direct knowledge entry by SMEs as an integrated team of technology developers.
The SRI team
includes Boeing, Information Sciences Institute (ISI) at University of Southern California, Northwestern University,Stanford
University,University of Massachusetts at Amherst, University of Texas at Austin, University of West Florida, Massachusetts
Institute of Technology, and Pragati Systems.
The claim of this effort is that SMEs, unassisted by ai technologists, can assemble models of mechanisms and processes from
components.
These models are both declarative and executable, so questions about the mechanisms and processes can be answered by
conventional inference methods (for example, theorem proving and taxonomic inference) and by various task-specific methods (for
example, simulation, analogical reasoning, and problem-solving methods).
A related claim is that relatively few components, perhaps
a few thousand, are sufficient for SMEs to assemble models of virtually any mechanism or process.
We claim that these components are
independent of domain, and that assembly from components instantiated to a domain is a natural way for SMEs to create KB content.
The research in this project exploits and extends previous work in the HPKB project, as well as work in process description
languages, qualitative physics, systems dynamics, and simulation.
One scientific innovation, and the principal extension to Cyc and
the "HPKB standard" of knowledge bases, is the idea of declarative and executable models (DEMs) assembled from components.
The
declarative aspect of DEMs supports conventional inference, whereas the executable aspect supports reasoning by simulation.
For
example, the declarative part of a model of aerosols is sufficient to answer questions like, "Will a 5-micron filter afford
protection against this aerosol?" while the executable part is necessary to model the dispersal pattern of the aerosol.
The development of libraries of components made available to SMEs via restricted natural language based, graphical, or templatized
interfaces is the principal means by which logic-oriented knowledge representation formalisms become accessible to ordinary users.
Every modeling technology shows this progression: Spreadsheets, finite-element packages, statistical packages, chemical synthesis
software, Macsyma and Mathematica, architectural and CAD packages, graphics and HCI systems, etc., are accessible to ordinary users
because they offer libraries of components.
As a practical matter, then, it makes sense to provide SMEs with libraries of modeling
components.
As a scientific matter, we believe we can develop components that represent how humans think about mechanisms and
processes.