Perhaps the most prominent current definition of (actual) causality is due to Halpern and Pearl. It is defined using causal models (also known as structural equations models). We abstract the definition, extracting its key features, so that it can be applied to any other model where counterfactuals are defined. By abstracting the definition, we gain a number of benefits. Not only can we apply the definition in a wider range of models, including ones that allow, for example, backtracking, but we can apply the definition to determine if A is a cause of B even if A and B are formulas involving disjunctions, negations, beliefs, and nested counterfactuals (none of which can be handled by the Halpern-Pearl definition). Moreover, we can extend the ideas to getting an abstract definition of explanation that can be applied beyond causal models. Finally, we gain a deeper understanding of features of the definition even in causal models.

翻译：当前最受关注的（实际）因果关系定义源于Halpern与Pearl的研究。该定义基于因果模型（亦称结构方程模型）构建。本文通过抽象化该定义，提取其核心特征，使其可应用于任何定义了反事实条件的其他模型。通过抽象化定义，我们获得了多重优势：不仅能在更广泛的模型（例如允许回溯推理的模型）中应用该定义，还能用于判定A是否为B的原因——即使A和B是包含析取、否定、信念及嵌套反事实的公式（这些情形均无法由Halpern-Pearl定义处理）。此外，我们可将该思路拓展至解释的抽象定义，使其适用于因果模型之外的场景。最终，即使在因果模型中，我们也能对定义的特征获得更深刻的理解。