论文标题
如何通过不一致的概率信息来推理？
How to reason with inconsistent probabilistic information?
论文作者
论文摘要
根据证据，围绕信念逻辑发展了最近的一项研究。 Bílková等人的方法理解了基于可靠来源确认的信息的信念。我们提出了对信念如何基于信息的更精细分析，确认来自多个可能相互矛盾的来源，并且具有概率性质。我们使用Belnap-Dunn逻辑及其概率扩展来解释潜在的矛盾信息。我们将其与Lukasiewicz逻辑或Bilattice Logic的扩展结合在一起，在两层模态逻辑框架中以说明信念。
A recent line of research has developed around logics of belief based on evidence. The approach of Bílková et al understands belief as based on information confirmed by a reliable source. We propose a finer analysis of how belief can be based on information, where the confirmation comes from multiple possibly conflicting sources and is of a probabilistic nature. We use Belnap-Dunn logic and its probabilistic extensions to account for potentially contradictory information on which belief is grounded. We combine it with an extension of Lukasiewicz logic, or a bilattice logic, within a two-layer modal logical framework to account for belief.
