A Modification of the Halpern-Pearl Definition of Causality
Authors: Joseph Halpern
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, I further modify the HP definition, by placing more stringent restrictions on the contingencies that can be considered. Roughly speaking, when we consider various contingencies, I do not allow the values of variables other than that of the putative cause(s) to be changed; I simply allow values to be frozen at their actual values. This results in a definition that is significantly simpler than the HP definition, deals well with all the standard examples in the literature, and deals with some of the problem cases better than the HP definition. In addition, the complexity of computing causality is p, simpler than that of either the original HP definition or the modification proposed by HP (cf. [Aleksandrowicz et al., 2014; Eiter and Lukasiewicz, 2002]. |
| Researcher Affiliation | Academia | Joseph Y. Halpern Cornell University Computer Science Department Ithaca, NY 14853 halpern@cs.cornell.edu |
| Pseudocode | No | The paper uses mathematical and logical formulations but does not include any pseudocode or algorithm blocks. |
| Open Source Code | No | This is a theoretical paper focusing on formal definitions and proofs; it does not present software code for release. |
| Open Datasets | No | The paper uses conceptual examples and theoretical analysis; it does not utilize datasets for training or evaluation. |
| Dataset Splits | No | The paper focuses on theoretical definitions and examples rather than empirical experiments, so there is no mention of validation, training, or test data splits. |
| Hardware Specification | No | The paper is theoretical and does not involve computational experiments that would require hardware specifications. |
| Software Dependencies | No | The paper is theoretical; it does not report on implemented software or its dependencies. |
| Experiment Setup | No | The paper presents a theoretical modification of a definition of causality and analyzes it conceptually; there are no empirical experiments with a setup to describe. |