Explanation Capabilities of Production-Based Consultation Systems

Abstract

A computer program that models an expert in a given domain is more likely to be accepted by experts in that domain, and by non-experts seeking its advice, if the system can explain its actions. An explanation capability not only adds to the system's credibility, but also enables the non-expert user to learn from it. Furthermore, clear explanations allow an expert to check the system's 'reasoning', possibly discovering the need for refinements and additions to the system's knowledge base. In a developing system, an explanation capability can be used as a debugging aid to verify that additions to the system are working as they should. This paper discusses the general characteristics of explanation systems: what types of explanations they should be able to give, what types of knowledge will be needed in order to give these explanations, and how this knowledge might be organized. The explanation facility in MYCIN is discussed as an illustration of how the various problems might be approached.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1977
Accession Number
ADA042719

Entities

People

  • A. Carlisle Scott
  • Edward H. Shortliffe
  • Randall Davis
  • William J. Clancey

Organizations

  • Stanford University

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Anti-Bacterial Agents
  • Bacteria
  • Computer Programs
  • Computer Science
  • Computers
  • Databases
  • Dictionaries
  • Diseases And Disorders
  • Health Services
  • Infection
  • Infectious Diseases
  • Language
  • Natural Language Processing
  • Natural Languages
  • Production
  • Reasoning
  • Streptococcus

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence