Substantial efforts have been made in developing various Decision Modeling
formalisms, both from industry and academia. A challenging problem is that of
expressing decision knowledge in the context of incomplete knowledge. In such
contexts, decisions depend on what is known or not known. We argue that none of
the existing formalisms for modeling decisions are capable of correctly
capturing the epistemic nature of such decisions, inevitably causing issues in
situations of uncertainty. This paper presents a new language for modeling
decisions with incomplete knowledge. It combines three principles:
stratification, autoepistemic logic, and definitions. A knowledge base in this
language is a hierarchy of epistemic theories, where each component theory may
epistemically reason on the knowledge in lower theories, and decisions are made
using definitions with epistemic conditions.

本文提出了一种用于对不完全知识建模决策的新语言，它结合了分层、自知逻辑和定义三个原则，其中知识库是一个认识论理论的层级结构，每个组成部分理论都可以对较低理论中的知识进行认识论推理，并使用具有认识条件的定义来进行决策。