This paper addresses the integration of \emph{epistemic entrenchment} into paraconsistent belief revision systems based on Logics of Formal Inconsistency (LFIs). While systems like AGMp and AGM$\circ$ adapt AGM principles to paraconsistency, they lack mechanisms to rank beliefs, primarily due to the absence of properties such as the \emph{replacement property} in the underlying logics. We introduce two novel logics, \textbf{Cbr} and \textbf{RCBr}, with the latter extending the former to fully address these limitations given that it is self-extensional. Using \textbf{RCBr}, we define contraction operations via \emph{epistemic entrenchment}, adhering to key rationality principles. Our framework leverages non-deterministic matrix semantics (Nmatrices), providing a robust foundation for paraconsistent reasoning. These contributions advance the theory of paraconsistent belief revision and pave the way for applications in domains such as multi-agent systems and inconsistent knowledge bases.

翻译：本文探讨将**认知固守性**整合至基于形式不一致逻辑的次协调信念修正系统中。尽管AGMp和AGM∘等系统将AGM原则适配于次协调性，但由于底层逻辑缺乏**替换性质**等属性，它们缺乏对信念进行排序的机制。我们引入两种新颖逻辑**Cbr**和**RCBr**，其中后者作为自外延逻辑对前者进行扩展，以全面解决这些局限。基于**RCBr**，我们通过**认知固守性**定义了满足关键理性原则的收缩运算。本框架采用非确定性矩阵语义学作为基础，为次协调推理提供了坚实支撑。这些成果推进了次协调信念修正理论的发展，并为多智能体系统和不一致知识库等领域的应用铺平了道路。