Langlotz C P
Section on Medical Informatics, Stanford University School of Medicine, CA 94305-5479.
Comput Methods Programs Biomed. 1989 Oct-Nov;30(2-3):85-95. doi: 10.1016/0169-2607(89)90061-8.
We distinguish axiomatically-based expert systems, whose design and implementation are guided by one or more axiomatically-based theories of decision-making (e.g., decision theory, Bayesian probability theory, maximum entropy theory), from traditional expert systems. An analysis of the knowledge acquisition and computational needs of axiomatically-based expert systems is presented. An explicit quantitative comparison is made between the actual knowledge acquisition effort required to build an existing expert system, and the effort that would be required to build an analogous axiomatically-based advice system. The costs and benefits of the axiomatic approach are discussed. The analysis suggests that the small additional cost of knowledge acquisition for the axiomatic approach are outweighed by the long-term benefits this approach provides.
我们将基于公理的专家系统与传统专家系统区分开来，前者的设计和实现由一个或多个基于公理的决策理论（如决策理论、贝叶斯概率论、最大熵理论）指导。本文对基于公理的专家系统的知识获取和计算需求进行了分析。我们对构建一个现有专家系统所需的实际知识获取工作量与构建一个类似的基于公理的建议系统所需的工作量进行了明确的定量比较。讨论了公理方法的成本和收益。分析表明，公理方法在知识获取方面的少量额外成本被该方法带来的长期收益所抵消。
