Practical Decision Analytic Methods For Large Knowledge- Based Systems

大型知识系统的实用决策分析方法

• 批准号: 9120330
• 负责人: Max Henrion
• 金额: $ 59.5万
• 依托单位: Institute for Decision Systems Research
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-09-15 至 1996-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9120330&HistoricalAwards=false
• 关键词: Practical; Decision; Analytic; Methods; Large

Expert systems that perform diagnosis are being used increasingly in medicine, aerospace, and other high-stakes domains. Research has recently shown that heuristic schemes widely used in such systems to encode uncertain knowledge - used in diagnosis and decision making - can produce faulty reasoning. Schemes based on probability and decision analysis have been proposed as sounder; however, they have often then been dismissed as intractable. The goal of this research is to develop and evaluate new probabilistic and decision-analytic schemes, that are both sound and tractable. The planned products comprise methods for encoding uncertain knowledge in probabilistic form; for encoding judgments on values, costs, and preferences; efficient algorithms for probabilistic inference and decision making; and methods to generate comprehensible explanations of systems conclusions. These techniques are demonstrated and evaluated by application to two large knowledge-based systems, including a reformulation of QMR (Quick Medical Reference), a system for diagnosis in internal medicine; and a system for fault diagnosis and repair of gas turbines for power generation. These techniques are expected to lead to diagnostic expert systems that are easier to build and modify, that are more reliable, and that generate diagnostic test strategies that minimize unnecessary and expensive testing.

执行诊断的专家系统正越来越多地被用于医学、航空航天和其他高风险领域。最近的研究表明，在这类系统中广泛使用的启发式方案来编码不确定知识-用于诊断和决策-可能会产生错误的推理。基于概率和决策分析的方案被提出为更合理的方案；然而，它们随后往往被认为难以解决。这项研究的目标是开发和评估新的概率和决策分析方案，既合理又容易处理。计划中的产品包括：以概率形式编码不确定知识的方法；对价值、成本和偏好的判断进行编码的方法；概率推理和决策的有效算法；以及生成系统结论的可理解解释的方法。这些技术通过在两个大型基于知识的系统中的应用进行了演示和评估，其中包括一个用于内科诊断的QMR(快速医学参考)的重新制定系统，以及一个用于发电的燃气轮机故障诊断和维修系统。预计这些技术将导致诊断专家系统更容易建立和修改，更可靠，并产生诊断测试战略，最大限度地减少不必要和昂贵的测试。