论文标题
通过BELNAP- DUNN逻辑更新信念功能
Updating belief functions over Belnap--Dunn logic
论文作者
论文摘要
信念和合理性是不确定性的措施弱，而不是概率。当无法获得完整的概率信息时，它们的动机是出于情况。但是，信息也可能是矛盾的。因此，古典逻辑的框架不一定是最足够的。引入了Belnap-Dunn逻辑，以理论不完整和矛盾的信息。 Klein等人和Bilkova等人分别将概率措施和信念功能的概念分别为BELNAP-DUNN逻辑。在本文中，我们研究了如何使用新信息来更新信念功能。我们通过Belnap-Dunn Logic的框架语义提出了第一种方法。
Belief and plausibility are weaker measures of uncertainty than that of probability. They are motivated by the situations when full probabilistic information is not available. However, information can also be contradictory. Therefore, the framework of classical logic is not necessarily the most adequate. Belnap-Dunn logic was introduced to reason about incomplete and contradictory information. Klein et al and Bilkova et al generalize the notion of probability measures and belief functions to Belnap-Dunn logic, respectively. In this article, we study how to update belief functions with new pieces of information. We present a first approach via a frame semantics of Belnap-Dunn logic.
