Equivalent Causal Models

Authors

  • Sander Beckers Ludwig Maximilian University - Munich

Keywords:

Action, Change, and Causality

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.

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Published

2021-05-18

How to Cite

Beckers, S. (2021). Equivalent Causal Models. Proceedings of the AAAI Conference on Artificial Intelligence, 35(7), 6202-6209. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/16771

Issue

Section

AAAI Technical Track on Knowledge Representation and Reasoning