Qualitative Choice Logic (QCL) and Conjunctive Choice Logic (CCL) are formalisms for preference handling, with especially QCL being well established in the field of AI. So far, analyses of these logics need to be done on a case-by-case basis, albeit they share several common features. This calls for a more general choice logic framework, with QCL and CCL as well as some of their derivatives being particular instantiations. We provide such a framework, which allows us, on the one hand, to easily define new choice logics and, on the other hand, to examine properties of different choice logics in a uniform setting. In particular, we investigate strong equivalence, a core concept in non-classical logics for understanding formula simplification, and computational complexity. Our analysis also yields new results for QCL and CCL. For example, we show that the main reasoning task regarding preferred models of choice logic formulas is ${\mathrm{\Theta }}_2^{\mathsf{P}}$-complete for QCL and CCL, while being ${\mathrm{\Delta }}_2^{\mathsf{P}}$-complete for a newly introduced choice logic. The complexity of preferred model entailment for choice logic theories ranges from $\mathsf{coNP}$ to ${\mathrm{\Pi }}_2^{\mathsf{P}}$.

定性选择逻辑 (QCL) 和连接选择逻辑 (CCL) 是偏好处理的形式，尤其是 QCL 在人工智能领域得到了很好的建立。到目前为止，需要逐案分析这些逻辑，尽管它们具有几个共同的特征。这需要一个更通用的选择逻辑框架，其中 QCL 和 CCL 以及它们的一些衍生物是特定的实例化。我们提供了这样一个框架，一方面，它使我们能够轻松定义新的选择逻辑，另一方面，在统一的设置中检查不同选择逻辑的属性。特别是，我们研究了强等价性，这是非经典逻辑中用于理解公式简化和计算复杂性的核心概念。我们的分析还产生了 QCL 和 CCL 的新结果。例如，${\mathrm{\theta }}_2^{\mathsf{磷}}$-完成 QCL 和 CCL，同时${\mathrm{\Delta }}_2^{\mathsf{磷}}$-完成新引入的选择逻辑。选择逻辑理论的首选模型蕴涵的复杂性范围从$\mathsf{配比}$至${\mathrm{\Pi }}_2^{\mathsf{磷}}$.