A Logic for Global and Local Announcements

F. Belardinelli, H. V. Ditmarsch, W. Hoek
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引用次数: 3

Abstract

In this paper we introduce {\em global and local announcement logic} (GLAL), a dynamic epistemic logic with two distinct announcement operators -- $[\phi]^+_A$ and $[\phi]^-_A$ indexed to a subset $A$ of the set $Ag$ of all agents -- for global and local announcements respectively. The boundary case $[\phi]^+_{Ag}$ corresponds to the public announcement of $\phi$, as known from the literature. Unlike standard public announcements, which are {\em model transformers}, the global and local announcements are {\em pointed model transformers}. In particular, the update induced by the announcement may be different in different states of the model. Therefore, the resulting computations are trees of models, rather than the typical sequences. A consequence of our semantics is that modally bisimilar states may be distinguished in our logic. Then, we provide a stronger notion of bisimilarity and we show that it preserves modal equivalence in GLAL. Additionally, we show that GLAL is strictly more expressive than public announcement logic with common knowledge. We prove a wide range of validities for GLAL involving the interaction between dynamics and knowledge, and show that the satisfiability problem for GLAL is decidable. We illustrate the formal machinery by means of detailed epistemic scenarios.
全局和本地公告的逻辑
在本文中,我们引入了{\em全局和局部公告逻辑}(GLAL),它是一种动态认知逻辑,具有两个不同的公告算子- $[\phi]^+_A$和$[\phi]^-_A$,分别索引到所有智能体集合$Ag$的子集$ a $,用于全局和局部公告。边界情况$[\phi]^+_{Ag}$对应于文献中已知的$\phi$的公开声明。不像标准的公告是{\em模型转换器},全局和局部公告是{\em点模型转换器}。特别是,由公告引起的更新在模型的不同状态下可能是不同的。因此,得到的计算结果是模型树,而不是典型的序列。我们的语义学的一个结果是,模态双相似的状态可以在我们的逻辑中被区分出来。然后,我们提供了一个更强的双相似性概念,并证明它在GLAL中保持模态等价。此外,我们还证明了GLAL严格地比具有公共知识的公告逻辑更具表现力。我们证明了涉及动力学和知识相互作用的全局优化的广泛的有效性,并证明了全局优化的可满足性问题是可决定的。我们通过详细的认知情景来说明形式机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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