Kappa演算与概率推理的关系
On the Relation between Kappa Calculus and Probabilistic Reasoning
摘要：
我们研究了kappa演算和概率推理在诊断应用中的联系。具体来说，我们抽象的概率信念网络诊断故障到一个Kappa网络，并比较使用这两种方法计算的故障的顺序。我们表明，至少对于检查的例子，故障的顺序一致，只要考虑到所有的因果关系在原来的概率网络。我们还提供了一个正式的分析，一些网络结构，这两种方法将不同。Kappa等级和无穷小概率都被广泛用于研究缺省推理和信念修正。但是，在利用上述联系方面却做得很少。这部分是因为kappa和概率演算之间的关系假设概率任意接近于1（或0）。本文中的实验研究这种关系时，这个假设不满足。报告的结果有重要的影响，使用Kappa排名，以提高知识工程的不确定性模型。
英文摘要：
We study the connection between kappa calculus and probabilistic reasoning in diagnosis applications. Specifically, we abstract a probabilistic belief network for diagnosing faults into a kappa network and compare the ordering of faults computed using both methods. We show that, at least for the example examined, the ordering of faults coincide as long as all the causal relations in the original probabilistic network are taken into account. We also provide a formal analysis of some network structures where the two methods will differ. Both kappa rankings and infinitesimal probabilities have been used extensively to study default reasoning and belief revision. But little has been done on utilizing their connection as outlined above. This is partly because the relation between kappa and probability calculi assumes that probabilities are arbitrarily close to one (or zero). The experiments in this paper investigate this relation when this assumption is not satisfied. The reported results have important implications on the use of kappa rankings to enhance the knowledge engineering of uncertainty models.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
