NEURAL NETWORKS FOR DECISION-SUPPORT - PROBLEMS AND OPPORTUNITIES

Neural networks offer an approach to computing which - unlike conventi onal programming - does not necessitate a complete algorithmic specifi cation. Furthermore, neural networks provide inductive means for gathe ring, storing, and using, experiential knowledge. Incidentally, these have also been some of the fundamental motivations for the development of decision support systems in general. Thus, the interest in neural networks for decision support is immediate and obvious. In this paper, we analyze the potential contribution of neural networks for decision support, on one hand, and point out at some inherent constraints that might inhibit their use, on the other. For the sake of completeness a nd organization, the analysis is carried out in the context of a gener al-purpose DSS framework that examines all the key factors that come i nto play in the design of any decision support system.