A Knowledge based approach to active decision support

Abstract

As an efficient way of supporting high-level cognitive tasks, active decision supports have gained more attention in recent years. The major contribution of this thesis is to propose a knowledge-based approach to achieve active decision support. The approach is a new concept of intellectual support, which challenges the traditional way of solving a decision problem. It attempts at providing decision makers decisional guidance, which overcomes decision makers'fixation of considering only the feasible alternatives, suggests more alternatives and stimulates the discovery of opportunities lie in the alternatives overlooked by decision makers. Another active decision support idea based on statistical techniques is also included. The idea is to automatically refine the domain knowledge available for making efficient multi-criteria decisions through a serious of multivariate analysis tools. To illustrate these notions, the new methods are integrated in to a conceptual Knowledge-Based System (KBS) framework, which then be applied to R&D model management domain. Possibilities of applying the methods to other complex decision situations or enhance other decision-support tools are also discussed.