Adding fault tree analysis (FTA) into a knowledge: based problem solver

  • Authors:

  • F. A. Batzias;A. Bountri

  • Affiliations:

  • Department of Industrial Management and Technology, University of Piraeus, Piraeus, Greece;Department of Industrial Management and Technology, University of Piraeus, Piraeus, Greece

  • Venue:
  • AIKED'12 Proceedings of the 11th WSEAS international conference on Artificial Intelligence, Knowledge Engineering and Data Bases
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

The modern definition of Knowledge Engineering (KE) has been broadened by including design/structure, maintenance/enrichment and updating/restructuring/adaptation of knowledge-based systems. Two main views of KE are, nowadays, dominant: (i) the traditional transfer view, applying to transfer human knowledge/expertise into artificial intelligence (AI) systems, and (ii) the modeling or alternative view, attempting to model the knowledge and problem-solving techniques of the domain expert into the AI system. In this work, we extend the second view by incorporating Fault Tree Analysis (FTA) into a knowledge-based problem solver. The functionality of the methodological framework designed/developed for this purpose, under the form of an algorithmic procedure including 17 activity stages and 8 decision nodes, has been proved by implementing a case example referring to cultivated and waste biomass exploitation.