Task modeling with reusable problem-solving methods

Henrik Eriksson, Yuval Shahar, Samson W. Tu, Angel R. Puerta, Mark A. Musen

Research output: Contribution to journalArticlepeer-review

100 Scopus citations

Abstract

Problem-solving methods for knowledge-based systems establish the behavior of such systems by defining the roles in which domain knowledge is used and the ordering of inferences. Developers can compose problem-solving methods that accomplish complex application tasks from primitive, reusable methods. The key steps in this development approach are task analysis, method selection (from a library), and method configuration. Protégé-ii is a knowledge-engineering environment that allows developers to select and configure problem-solving methods. In addition, Protégé-ii generates domain-specific knowledge-acquisition tools that domain specialists can use to create knowledge bases on which the methods may operate. The board-game method is a problem-solving method that defines control knowledge for a class of tasks that developers can model in a highly specific way. The method adopts a conceptual model of problem solving in which the solution space is construed as a "game board" on which the problem solver moves "playing pieces" according to prespecified rules. This familiar conceptual model simplifies the developer's cognitive demands when configuring the board-game method to support new application tasks. We compare configuration of the board-game method to that of a chronological-backtracking problem-solving method for the same application tasks (for example, towers of Hanoi and the Sisyphus room-assignment problem). We also examine how method designers can specialize problem-solving methods by making ontological commitments to certain classes of tasks. We exemplify this technique by specializing the chronological-backtracking method to the board-game method.

Original languageEnglish
Pages (from-to)293-326
Number of pages34
JournalArtificial Intelligence
Volume79
Issue number2
DOIs
StatePublished - 1 Jan 1995
Externally publishedYes

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language
  • Artificial Intelligence

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