Equivalent Causal Models

4Citations
Citations of this article
16Readers
Mendeley users who have this article in their library.

Abstract

The aim of this paper is to offer the first systematic exploration and definition of equivalent causal models in the context where both models are not made up of the same variables. The idea is that two models are equivalent when they agree on all “essential” causal information that can be expressed using their common variables. I do so by focussing on the two main features of causal models, namely their structural relations and their functional relations. In particular, I define several relations of causal ancestry and several relations of causal sufficiency, and require that the most general of these relations are preserved across equivalent models.

Cite

CITATION STYLE

APA

Beckers, S. (2021). Equivalent Causal Models. In 35th AAAI Conference on Artificial Intelligence, AAAI 2021 (Vol. 7, pp. 6202–6209). Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/aaai.v35i7.16771

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free