基于抽象的诊断贝叶斯网络冲突检测
On the Detection of Conflicts in Diagnostic Bayesian Networks Using Abstraction
摘要：
使用专家系统的一个重要问题是所谓的脆性问题。专家系统只能模拟世界上有限的一部分。虽然专家系统中对不确定性的明确管理缓解了脆性问题，但系统仍有可能在无意中以系统不准备解决的方式被使用。这种情况可以通过吸管模型的方法来检测，该方法首先由Jensen等人[1990]提出，后来由Laskey [1991]推广和证明。我们描述了一种算法，我们已经实现，作为输入的注释诊断贝叶斯网络（基础模型）和结构，没有援助，二分网络被用作稻草模型。我们表明，在某些情况下，这个稻草模型是更好的独立稻草模型的Jensen等人，唯一的其他秸秆模型的建设算法已经设计和实施。
英文摘要：
An important issue in the use of expert systems is the so-called brittleness problem. Expert systems model only a limited part of the world. While the explicit management of uncertainty in expert systems itigates the brittleness problem, it is still possible for a system to be used, unwittingly, in ways that the system is not prepared to address. Such a situation may be detected by the method of straw models, first presented by Jensen et al. [1990] and later generalized and justified by Laskey [1991]. We describe an algorithm, which we have implemented, that takes as input an annotated diagnostic Bayesian network (the base model) and constructs, without assistance, a bipartite network to be used as a straw model. We show that in some cases this straw model is better that the independent straw model of Jensen et al., the only other straw model for which a construction algorithm has been designed and implemented.
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