Related papers: New Rules for Causal Identification with Background Knowledge

New Rules for Causal Identification with Background Knowledge

URL: http://arxiv.org/abs/2407.15259v1
Date: Sun, 21 Jul 2024 20:21:21 GMT
Title: New Rules for Causal Identification with Background Knowledge
Authors: Tian-Zuo Wang, Lue Tao, Zhi-Hua Zhou,
Abstract summary: We propose two novel rules for incorporating BK, which offer a new perspective to the open problem. We show that these rules are applicable in some typical causality tasks, such as determining the set of possible causal effects with observational data.
Score: 59.733125324672656
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: Identifying causal relations is crucial for a variety of downstream tasks. In additional to observational data, background knowledge (BK), which could be attained from human expertise or experiments, is usually introduced for uncovering causal relations. This raises an open problem that in the presence of latent variables, what causal relations are identifiable from observational data and BK. In this paper, we propose two novel rules for incorporating BK, which offer a new perspective to the open problem. In addition, we show that these rules are applicable in some typical causality tasks, such as determining the set of possible causal effects with observational data. Our rule-based approach enhances the state-of-the-art method by circumventing a process of enumerating block sets that would otherwise take exponential complexity.

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