We characterize four types of agentive knowledge using a stit semantics over branching discrete-time structures. These are ex ante knowledge, ex interim knowledge, ex post knowledge, and know-how. The first three are notions that arose from game-theoretical analyses on the stages of information disclosure across the decision making process, and the fourth has gained prominence both in logics of action and in deontic logic as a means to formalize ability. In recent years, logicians in AI have argued that any comprehensive study of responsibility attribution and blameworthiness should include proper treatment of these kinds of knowledge. This paper intends to clarify previous attempts to formalize them in stit logic and to propose alternative interpretations that in our opinion are more akin to the study of responsibility in the stit tradition. The logic we present uses an extension with knowledge operators of the Xstit language, and formulas are evaluated with respect to branching discrete-time models. We also present an axiomatic system for this logic, and address its soundness and completeness.

我们使用分支离散时间结构上的 stit 语义来表征四种类型的代理知识。这些都是事前知识，前中期的知识，事后知识和诀窍。前三个概念源自对决策过程中信息披露阶段的博弈论分析，第四个概念在行动逻辑和道义逻辑中都获得了突出地位，作为将能力形式化的一种手段。近年来，人工智能领域的逻辑学家认为，任何对责任归属和可责性的综合研究都应该包括对这些知识的正确处理。本文旨在澄清先前在 stit 逻辑中将它们形式化的尝试，并提出在我们看来更类似于 stit 传统中的责任研究的替代解释。我们提出的逻辑使用 Xstit 语言知识运算符的扩展，并根据分支离散时间模型评估公式。