Problem-Solving Models for Generation of Task-Specific Knowledge-Acquisition Tools

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Citation: Mark A. Musen. (1993) Problem-Solving Models for Generation of Task-Specific Knowledge-Acquisition Tools. In KSL-91-05, January,1993.

Publication techreport ( Edit )
type Technical Report
bibtype techreport
Bibtex basics
author Mark A. Musen
title Problem-Solving Models for Generation of Task-Specific Knowledge-Acquisition Tools
number KSL-91-05
institution Knowledge Systems, AI Laboratory
year 1993
month January
Bibtex more
note Medical Computer Science
Access Paper
abstract Much current work on knowledge acquisition for intelligent systems concentrates on the use of predefined models of problem-solving methods to define the roles in which domain knowledge is used to solve particular application tasks. Knowledge-acquisition tools that incorporate such models impose task-specific architectures on the knowledge bases that the tools are used to construct. PROTÉGÉ-I is a metalevel program that generates knowledge-acquisition tools tailored for classes of application tasks. PROTÉGÉ-I includes a model of problem solving via the method of episodic skeletal-plan refinement (ESPR). Knowledge engineers extend this model of problem solving with domain knowledge to define models of relevant application areas. Current research in our laboratory concerns a new architecture, PROTÉGÉ-II, in which knowledge engineers assemble the ESPR model using a library of smaller building blocks, called problem-solving mechanisms. In addition to providing flexibility in the definition of the control strategy for the expert systems that PROTÉGÉ-II ultimately generates, the new architecture allows knowledge engineers to represent static domain knowledge as explicit ontologies of concepts and relationships that may themselves be reusable.

KSL Technical Report ID: KSL-91-05
Facts about Problem-Solving Models for Generation of Task-Specific Knowledge-Acquisition ToolsRDF feed
Abstract Much current work on knowledge acquisition … Much current work on knowledge acquisition for intelligent systems concentrates on the use of predefined models of problem-solving methods to define the roles in which domain knowledge is used to solve particular application tasks. Knowledge-acquisition tools that incorporate such models impose task-specific architectures on the knowledge bases that the tools are used to construct. PROTÉGÉ-I is a metalevel program that generates knowledge-acquisition tools tailored for classes of application tasks. PROTÉGÉ-I includes a model of problem solving via the method of episodic skeletal-plan refinement (ESPR). Knowledge engineers extend this model of problem solving with domain knowledge to define models of relevant application areas. Current research in our laboratory concerns a new architecture, PROTÉGÉ-II, in which knowledge engineers assemble the ESPR model using a library of smaller building blocks, called problem-solving mechanisms. In addition to providing flexibility in the definition of the control strategy for the expert systems that PROTÉGÉ-II ultimately generates, the new architecture allows knowledge engineers to represent static domain knowledge as explicit ontologies of concepts and relationships that may themselves be reusable. tionships that may themselves be reusable.
Author Mark A. Musen  +
Bibtype techreport  +
Has author Mark A. Musen  +
Has identifier KSL-91-05  +
Has publishing details January,1993  +
Has title Problem-Solving Models for Generation of Task-Specific Knowledge-Acquisition Tools  +
Has where published KSL-91-05  +
Has year 1993  +
Institution Knowledge Systems, AI Laboratory  +
Ksl tr id KSL-91-05  +
Month January  +
Note Medical Computer Science
Number KSL-91-05  +
Process note NO  +
Title Problem-Solving Models for Generation of Task-Specific Knowledge-Acquisition Tools  +
Year 1993  +
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