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An ontology of physical causation as a basis for assessing causation in fact and attributing legal responsibility

An ontology of physical causation as a basis for assessing causation in fact and attributing... Computational machineries dedicated to the attribution of legal responsibility should be based on (or, make use of) a stack of definitions relating the notion of legal responsibility to a number of suitably chosen causal notions. This paper presents a general analysis of legal responsibility and of causation in fact based on Hart and Honoré’s work. Some physical aspects of causation in fact are then treated within the “lite” version of DOLCE foundational ontology written in OWL-DL, a standard description logic for the Semantic Web. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Artificial Intelligence and Law Springer Journals

An ontology of physical causation as a basis for assessing causation in fact and attributing legal responsibility

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Publisher
Springer Journals
Copyright
Copyright © 2007 by Springer Science+Business Media B.V.
Subject
Computer Science; Artificial Intelligence (incl. Robotics); International IT and Media Law, Intellectual Property Law; Philosophy of Law; Legal Aspects of Computing; Information Storage and Retrieval
ISSN
0924-8463
eISSN
1572-8382
DOI
10.1007/s10506-007-9035-3
Publisher site
See Article on Publisher Site

Abstract

Computational machineries dedicated to the attribution of legal responsibility should be based on (or, make use of) a stack of definitions relating the notion of legal responsibility to a number of suitably chosen causal notions. This paper presents a general analysis of legal responsibility and of causation in fact based on Hart and Honoré’s work. Some physical aspects of causation in fact are then treated within the “lite” version of DOLCE foundational ontology written in OWL-DL, a standard description logic for the Semantic Web.

Journal

Artificial Intelligence and LawSpringer Journals

Published: Mar 7, 2007

References