Diagnostic Reasoning with Multilevel Set-Covering Models

Abstract

We consider multilevel set-covering models for diagnostic reasoning: though a lot of work has been done in this field, knowledge acquisition efforts have been investigated only insufficiently. We will show how set-covering models can be build incrementally and how they can be refined by knowledge enhancements or representational extensions. All these extensions have a primary characteristic: they can be applied without changing the basic semantics of the model.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
May 04, 2002
Accession Number
ADP012694

Entities

People

  • Dietmar Seipel
  • Joachim Baumeister

Organizations

  • University of Würzburg

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acquisition
  • Computations
  • Computer Science
  • Coverings
  • Demographic Cohorts
  • Engineering
  • Generators
  • Hypotheses
  • Learning
  • Machine Learning
  • Neural Networks
  • Observation
  • Precision
  • Reasoning
  • Semantics
  • Software Development
  • Technical Information Centers

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Computational Modeling and Simulation
  • Critical Infrastructure Protection in CBRN and WMD Threats.