Ill-definition, uncertainty and multiple objectives are primary characteristics of real-world decision-making processes. During the initial stages of such processes little knowledge appertaining to the problem at hand may be available. A primary task relates to improving problem definition in terms of variables, constraint and both quantitative and qualitative objectives. The problem space develops with information gained in a dynamical process where optimisation plays a secondary role following the establishment of a well-defined problem domain. The paper speculates upon the role of evolutionary computing, complementary computational intelligence techniques and interactive systems that support such problem definition where multiobjective satisfaction plays a major role.
CITATION STYLE
Parmee, I. C. (2001). Poor-definition, uncertainty, and human factors-satisfying multiple objectives in real-world decision-making environments. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1993, pp. 52–66). Springer Verlag. https://doi.org/10.1007/3-540-44719-9_4
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