Probabilistic Reasoning Across the Causal Hierarchy
Authors: Duligur Ibeling, Thomas Icard10170-10177
AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We propose a formalization of the three-tier causal hierarchy of association, intervention, and counterfactuals as a series of probabilistic logical languages. Our languages are of strictly increasing expressivity, the first capable of expressing quantitative probabilistic reasoning including conditional independence and Bayesian inference the second encoding docalculus reasoning for causal effects, and the third capturing a fully expressive do-calculus for arbitrary counterfactual queries. We give a corresponding series of finitary axiomatizations complete over both structural causal models and probabilistic programs, and show that satisfiability and validity for each language are decidable in polynomial space. |
| Researcher Affiliation | Academia | Duligur Ibeling,1 Thomas Icard2 1Department of Computer Science, Stanford University 2Department of Philosophy, Stanford University |
| Pseudocode | No | The paper describes logical languages and axiomatizations, but it does not include any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper discusses 'open-source code' in the context of other research and tools (e.g., Pyro), but it does not provide an explicit statement or link for the open-sourcing of its own methodology's code. |
| Open Datasets | No | This is a theoretical paper focusing on logical languages and axiomatizations; it does not involve training models on datasets. Therefore, there is no discussion of dataset availability for training. |
| Dataset Splits | No | This is a theoretical paper focusing on logical languages and axiomatizations; it does not involve data partitioning for validation. It mentions 'satisfiability and validity' as logical concepts, not data splits. |
| Hardware Specification | No | The paper is theoretical and does not report on computational experiments that would require specific hardware. No hardware specifications are mentioned. |
| Software Dependencies | No | The paper refers to mathematical methods (e.g., 'semialgebraic geometry', 'cylindrical algebraic decomposition') and other research tools (e.g., 'Pyro'), but it does not list specific software dependencies with version numbers for its own work. |
| Experiment Setup | No | The paper is theoretical and does not involve experimental setups with hyperparameters or training configurations. |