Unveiling the Structure of Do-Calculus Reasoning via Derivation Graphs
The paper introduces derivation graphs to enhance the understanding of do-calculus reasoning. These graphs help in representing the application and combination of do-calculus rules, simplifying the inference process. The authors also demonstrate how identification algorithms can yield multiple valid estimands for causal quantities, leading to more efficient estimators.
- ▪Derivation graphs represent how do-calculus rules are applied and combined.
- ▪The structure of these graphs allows for a simple procedure using at most four applications of do-calculus rules.
- ▪Applying identification algorithms to equivalent causal queries produces multiple valid estimands for the same causal quantity.
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| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2606.03719 |
| Publication time | Wed, 03 Jun 2026 00:00:00 -0400 |
| Retrieval time | 2026-06-03T04:11:55.408Z |
| Last seen | 2026-06-03T04:11:55.408Z |
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Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
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Computer Science > Artificial Intelligence arXiv:2606.03719 (cs) [Submitted on 2 Jun 2026] Title:Unveiling the Structure of Do-Calculus Reasoning via Derivation Graphs Authors:Clément Yvernes, Emilie Devijver, Marianne Clausel, Eric Gaussier View a PDF of the paper titled Unveiling the Structure of Do-Calculus Reasoning via Derivation Graphs, by Cl\'ement Yvernes and 3 other authors View PDF Abstract:The do-calculus defines a general system of inference for interventional queries, allowing causal quantities to be transformed through successive applications of its rules. This process induces a rich space of equivalent interventional expressions, but combining and ordering these rules remains challenging.
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