Adding Fault Tree Analysis (FTA) into a Knowledge - Based Problem Solver

摘要

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.