计算机科学 ›› 2016, Vol. 43 ›› Issue (9): 87-90.doi: 10.11896/j.issn.1002-137X.2016.09.016
• 2015 年第三届CCF 大数据学术会议 • 上一篇 下一篇
孟华,原雅燕,储节磊,王红军
MENG Hua, YUAN Ya-yan, CHU Jie-lei and WANG Hong-jun
摘要： 当agent的信念集是无限集时,传统的基于有限逻辑语言的刻画信念变化(belief change)的简单语义模型通常不再适用。Grdenfors和Makinson 引入的epistemic entrenchment(认知牢固度)模型虽然可以用来从语义上刻画AGM型信念收缩算子,但他们并未给出如何构造一个具体的epistemic entrenchment 的方法。在无限命题逻辑语言的背景下,通过在模型集上引入一个拓扑结构,构造出一种新的用来刻画AGM信念收缩的语义结构,称为认知链,并给出相应表示定理。讨论了epistemic entrenchment与认知链之间的关系。相对epistemic entrenchment而言,认知链具有结构简单并易于构造的特点。
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