A knowledge-based DSS for supporting ill-structured multiple criteria decisions

Abstract

Focusing on qualitative reasoning processes as a key area of A1 (artificial intelligence) application for decision support, the authors propose an architecture for designing an intelligent DSS (decision-support system) that is intended to aid in MCDM (multiple-criteria decision making) in ill-structured situations. An MCDM DSS, for its maximum contribution to organizational problem-solving, must be capable of lending effective support to high-level as well as low-level management decisions. A commercial loan approval judgement case is described to illustrate the real-world situation where decisions usually require a high degree of intuition and subjective judgement. Development of a prototype intended to partially represent application of the architecture is described. The authors conclude with suggestions for research extensions.<>