Reasoning about Causal Models with Infinitely Many Variables
Authors: Joseph Y. Halpern, Spencer Peters5668-5675
AAAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We provide a sound and complete axiomatization of causal reasoning in GSEMs that is an extension of the sound and complete axiomatization provided by Halpern (2000) for SEMs. Considering GSEMs helps clarify what properties Halpern s axioms capture. |
| Researcher Affiliation | Academia | Joseph Y. Halpern, Spencer Peters Cornell University halpern@cs.cornell.edu, sp2473@cornell.edu |
| Pseudocode | No | The paper defines axioms and logical rules but does not provide structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code. The URL provided is for the paper itself on arXiv, not for any code. |
| Open Datasets | No | This is a theoretical paper focused on axiomatization; it does not involve datasets or training. |
| Dataset Splits | No | This is a theoretical paper focused on axiomatization; it does not involve datasets or validation splits. |
| Hardware Specification | No | This is a theoretical paper; it does not describe any experimental setup or hardware used. |
| Software Dependencies | No | This is a theoretical paper; it does not describe any experimental setup or software dependencies. |
| Experiment Setup | No | This is a theoretical paper; it does not describe any experimental setup. |