The University of Edinburgh -
Division of Informatics
Forrest Hill & 80 South Bridge

MSc Thesis #92132

Title:Pdq: a Knowledge Based System to Help Knowledge-Based System Designers to Select Knowledge Representation and Inference Techniques
Date: 1992
Abstract:A knowledge-based system (KBS) to help KBS designers to select knowledge representation and inference (KRI) techniques is described. The system, called PDQ, elicits answers to questions concerning the functional requirements of the KBS to be designed, and it outputs recommendations for design features (KRI techniques) to be used to implement them. PDQ accumulates weight of evidence for and against design features, and the solutions it provides are the names of design features each with an attached positive or negative score to indicate the degree to which the system recommends or advises against its use. PDQ's knowledge was elicited from present and former members of staff at the Artificial Intelligence Applications Institute and the Department of Artificial Intelligence at the University of Edinburgh. It is a rule-based, data-driven system implemented in CLIPS. Knowledge elicitation and analysis were influenced by the work of Kline and Dolins [Kline & Dolins 89] on "probing questions" for KBS designers. However, the content of PDQ's rule-base is substantially independent of their work. While PDQ is not dedicated to any particular KBS development method, it is seen as a useful complement to the design phase of the KADS method.

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