On the Complexity of Counterfactual Reasoning
Authors: Yunqiu Han, Yizuo Chen, Adnan Darwiche
IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We finally present empirical results in Section 7 which reveal that, on average, the complexity gap between counterfactual and associational/interventional reasoning on fully specified SCMs can be smaller than what our worst-case bounds may suggest. 7 Experimental Results We consider experiments that target random networks whose structures emulate the structures of SCMs used in counterfactual reasoning. |
| Researcher Affiliation | Academia | Yunqiu Han , Yizuo Chen , Adnan Darwiche University of California, Los Angeles yunqiu21@g.ucla.edu, yizuo.chen@ucla.edu, darwiche@cs.ucla.edu |
| Pseudocode | Yes | Algorithm 1 Jointree to Twin Jointree |
| Open Source Code | No | No explicit statement providing access to the source code for the methodology described in this paper was found. |
| Open Datasets | No | The paper describes methods for generating random networks ('We generated random networks according to the method used in [Darwiche, 2020].' and 'We also included experiments using random networks generated according to the method in [Ide and Cozman, 2002].'), but does not provide concrete access information (link, DOI, repository, or formal citation with authors/year) for a publicly available or open dataset used for training or evaluation. |
| Dataset Splits | No | The paper describes generating random networks and evaluating their properties, but does not mention specific training, validation, or test dataset splits. |
| Hardware Specification | No | No specific hardware details (GPU/CPU models, memory, or detailed computer specifications) used for running experiments were mentioned in the paper. |
| Software Dependencies | No | No specific ancillary software details (e.g., library or solver names with version numbers) needed to replicate the experiment were provided. |
| Experiment Setup | Yes | We used n {50, 75, 100, 125, 150, 200, 250, 300} and p {3, 5, 7}. For each combination of n and p, we generated 50 random, base networks and reported averages of two properties for the constructed jointrees: width and normalized width. We use the popular minfill heuristic [Kjaerulff, 1990] in our experiments. |