Counterfactual Causality from First Principles?

Gregor Gössler 1 Oleg Sokolsky 2 Jean-Bernard Stefani 1
1 SPADES - Sound Programming of Adaptive Dependable Embedded Systems
Inria Grenoble - Rhône-Alpes
2 University of Pennsylvania [Philadelphia]
Abstract : In this position paper we discuss three main shortcomings of existing approaches to counterfactual causality from the computer science perspective, and sketch lines of work to try and overcome these issues: (1) causality definitions should be driven by a set of precisely specified requirements rather than specific examples; (2) causality frameworks should support system dynamics; (3) causality analysis should have a well-understood behavior in presence of abstraction.
Type de document :
Communication dans un congrès
2nd International Workshop on Causal Reasoning for Embedded and safety-critical Systems Technologies (CREST 2017), 2017, Uppsala, Sweden. 259, pp.47 - 53, 2017, 〈10.4204/EPTCS.259.5〉
Liste complète des métadonnées
https://hal.inria.fr/hal-01631415
Contributeur : Gregor Gössler <>
Soumis le : jeudi 9 novembre 2017 - 11:11:07
Dernière modification le : mercredi 11 avril 2018 - 01:54:33

Lien texte intégral

arxiv

Identifiants

Collections

INRIA | INRIA2017 | INRIA-RENGRE

Citation

Gregor Gössler, Oleg Sokolsky, Jean-Bernard Stefani. Counterfactual Causality from First Principles?. 2nd International Workshop on Causal Reasoning for Embedded and safety-critical Systems Technologies (CREST 2017), 2017, Uppsala, Sweden. 259, pp.47 - 53, 2017, 〈10.4204/EPTCS.259.5〉. 〈hal-01631415〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

46

Contact


archive-ouverte@inria.fr