Computer Science Department, University of California, Los Angeles 90095-1596, USA.
Cogn Sci. 2013 Aug;37(6):977-85. doi: 10.1111/cogs.12065.
Recent advances in causal reasoning have given rise to a computational model that emulates the process by which humans generate, evaluate, and distinguish counterfactual sentences. Contrasted with the "possible worlds" account of counterfactuals, this "structural" model enjoys the advantages of representational economy, algorithmic simplicity, and conceptual clarity. This introduction traces the emergence of the structural model and gives a panoramic view of several applications where counterfactual reasoning has benefited problem areas in the empirical sciences.
近年来，因果推理领域的进展催生了一种计算模型，该模型模拟了人类生成、评估和区分反事实句子的过程。与反事实的“可能世界”解释相比，这种“结构”模型具有表示经济、算法简单和概念清晰的优势。本引言追溯了结构模型的出现，并全面介绍了反事实推理在经验科学的一些受益问题领域的几个应用。
