时间因果推理与非递归结构方程模型 (Temporal Causal Reasoning with (Non-Recursive) Structural Equation Models)

from arxiv, This is an extended version of the same title paper published in the proceeding of AAAI-25 conference (Gladyshev et al. 2025). This version contains an additional section, in which we introduce TSEMs with arbitrary long temporal delays between causal dependencies and prove that these models are equivalent to TSEMs with 1-step delays only introduced in the original version of the paper

Structural Equation Models (SEM) are the standard approach to representing causal dependencies between variables in causal models. In this paper we propose a new interpretation of SEMs when reasoning about Actual Causality, in which SEMs are viewed as mechanisms transforming the dynamics of exogenous variables into the dynamics of endogenous variables. This allows us to combine counterfactual causal reasoning with existing temporal logic formalisms, and to introduce a temporal logic, CPLTL, for causal reasoning about such structures. We show that the standard restriction to so-called \textit{recursive} models (with no cycles in the dependency graph) is not necessary in our approach, allowing us to reason about mutually dependent processes and feedback loops. Finally, we introduce new notions of model equivalence for temporal causal models, and show that CPLTL has an efficient model-checking procedure.

翻译：结构方程模型（SEM）是因果模型中表示变量间因果依赖关系的标准方法。本文针对实际因果推理提出了一种新的SEM解释框架，将SEM视为将外生变量动态转化为内生变量动态的机制。这一视角使我们能够将反事实因果推理与现有时序逻辑形式体系相结合，并引入一种新的时序逻辑CPLTL用于此类结构的因果推理。我们证明，传统方法中对所谓"递归"模型（依赖图中无环）的限制在本方法中并非必要，从而能够推理相互依赖过程与反馈循环。最后，我们提出了时序因果模型的新等价概念，并证明CPLTL具有高效的模型检验算法。