On Open-Universe Causal Reasoning
Not on the map. Why?
Abstract (arXiv)
We extend two kinds of causal models, structural equation models and simulation models, to infinite variable spaces. This enables a semantics for conditionals founded on a calculus of intervention, and axiomatization of causal reasoning for rich, expressive generative models -- including those in which a causal representation exists only implicitly -- in an open-universe setting. Further, we show that under suitable restrictions the two kinds of models are equivalent, perhaps surprisingly as their axiomatizations differ substantially in the general case. We give a series of complete axiomatizations in which the open-universe nature of the setting is seen to be essential.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 4 Jul 2019.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 3; 2022: 0; 2023: 0; 2024: 0; 2025: 3.
6 papers.
- 2025How Causal Abstraction Underpins Computational Explanationcited by 11
- 2021A Topological Perspective on Causal Inferencecited by 10
- 2021Causal Modeling With Infinitely Many Variablescited by 7
- 2025Punctuation and Predicates in Language Modelscited by 5
- 2021Observing Interventions: A logic for thinking about experimentscited by 1
- 2025Causality in the human niche: lessons for machine learningcited by 1
- 2025How Causal Abstraction Underpins Computational Explanation15 Aug 2025
- 2025Punctuation and Predicates in Language Models11 Aug 2025
- 2025Causality in the human niche: lessons for machine learning13 Jun 2025
- 2021Causal Modeling With Infinitely Many Variables16 Dec 2021
- 2021Observing Interventions: A logic for thinking about experiments25 Nov 2021
- 2021A Topological Perspective on Causal Inference18 Jul 2021