Automating Knowledge Acquisition and Refinement for Decision Support: A Connectionist Inductive Inference Model*
针对非结构化决策中启发式知识难以获取的问题，提出一种结合归纳推理与神经网络计算的模型，并通过示例展示其在非结构化决策支持中的潜力。
ABSTRACT An important application of expert systems technology is to provide support for nonstructured decision making. Usually, nonstructured decision making is characterized by heavy reliance on heuristic knowledge, which is very difficult to articulate or document, and therefore traditional knowledge acquisition approaches are not very successful. The quality and effectiveness of an expert system supporting unstructured decision making is affected when traditional knowledge acquisition approaches are used. To alleviate this problem a model is proposed that combines inductive inference and neural network computing, and an example is presented that illustrates the potential of this model in unstructured decision support.