Actual Causality in a Logical Setting
Authors: Alexander Bochman
IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We provide a definition of actual causation in the logical framework of the causal calculus, which is based on a causal version of the well-known NESS (or INUS) condition. We compare our definition with other, mainly counterfactual, approaches on standard examples. On the way, we explore general capabilities of the logical representation for structural equation models of causation and beyond. |
| Researcher Affiliation | Academia | Alexander Bochman Computer Science Department, Holon Institute of Technology, Israel bochmana@hit.ac.il |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link regarding the availability of open-source code for the described methodology. |
| Open Datasets | No | The paper discusses 'standard examples' from the literature to illustrate its theoretical definitions but does not use or provide access to a public dataset in the context of training or evaluation. |
| Dataset Splits | No | The paper is theoretical and does not describe experiments with data. Therefore, it does not provide details on training, validation, or test dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not describe experiments that would require hardware specifications. No hardware details are mentioned. |
| Software Dependencies | No | The paper is theoretical and does not describe experiments or implementations that would require specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe experimental setups, hyperparameters, or training configurations. |