The structural model interpretation of the NESS Test

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3060, Issue , 2014, Pages 292-307

  Baldwin, Richard A ^a   Neufeld, Eric ^a  

^a UNIVERSITY OF SASKATCHEWAN   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE;

CAUSAL ATTRIBUTIONS; MATHEMATICAL LANGUAGES; OVERDETERMINATION; STRUCTURAL MODELING; STRUCTURAL MODELS;

TESTING;

EID: 7444252376     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-24840-8_21     Document Type: Conference Paper

References (13)

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2. Baldwin, Richard (2003). A Structural Model Interpretation of Wright's NESS test. Department of Computer Science, University of Saskatchewan, MSc thesis [Online]. Available: http://library.usask.ca/theses/available/etd-09152003-154313/ [Accessed 2003, Nov. 28].
3. Baldwin, R., and Neufeld, E. (2003) On the Structure Model Interpretation of Wright's NESS Test. In Proceedings of AI 2003, Halifax (June 2003) LNAI 2671 9-23
4. Wright, R.W. (1985). Causation in tort law. California Law Review, 73, pp. 1735-1828.
5. Halpern, J.Y., and Pearl, J. (2000). Causes and explanations: a structural-model approach. Retrieved September 3, 2001 from http://www.cs.cornell.edu/home/halpern/topics.html#rau (Part I, Causes, appears in Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence, San Francisco, CA: Morgan Kaufmann, 194-202, 2001.)
6. Hart, H.L.A., and Honoré, A.M. (1985). Causation in the law (2nd ed.). Oxford University Press.
7. Hopkins, M., and Pearl, J. (2003). Clarifying the Usage of Structural Models for Commonsense Causal Reasoning. In Proceedings of the 2003 AAAI Spring Symposium on Logical Formalizations of Commonsense Reasoning, Stanford University, March 24-26, 2003.
8. Pearl, J. (1995). Causal diagrams for empirical research. Biometrika, 82 (4), 669-710.
9. Pearl, J. (1998). On the definition of actual cause. Technical Report (no. R-259), Department of Computer Science, University of California, Los Angeles.
10. Pearl, J. (2000). Causality: Models, reasoning, and inference. New York: Cambridge University Press.
11. Wright, R.W. (1985). Causation in tort law. California Law Review, 73, pp. 1735-1828.
12. Wright, R.W. (1988). Causation, responsibility, risk, probability, naked statistics, and proof: Pruning the bramble bush by clarifying the concepts. Iowa Law Review, 73, pp. 1001-1077.
13. Wright, R.W. (2001). Once more into the bramble bush: Duty, causal contribution, and the extent of legal responsibility [Electronic version]. Vanderbilt Law Review, 54 (3), pp. 1071-1132.