Strategies for determining causes of events

Proceedings of the National Conference on Artificial Intelligence

Volumn , Issue , 2002, Pages 546-552

  Hopkins, Mark ^a  

^a University of California   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; PROBLEM SOLVING; THEOREM PROVING;

CAUSAL MODELS;

MATHEMATICAL TECHNIQUES;

EID: 0036926359     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

1. Eiter, T., and Lukasiewicz, T. 2001. Complexity results for structure-based causality. In In Proceedings of the International Joint Conference on Artificial Intelligence, 35-40. San Francisco, CA: Morgan Kaufmann.
2. Halpern, J., and Pearl, J. 2001. Causes and explanations: A structural-model approach-parti: Causes. In. Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence, 194-202. San Francisco, CA: Morgan Kaufmann.
3. Hopkins, M. 2002a. A proof of the conjunctive cause conjecture in 'causes and explanations: A structural-model approach'. Technical Report R-306, UCLA Cognitive Systems Laboratory.
4. Hopkins, M. 2002b. Strategies for determining causes of events. Technical Report R-302-L, UCLA Cognitive Systems Laboratory.
5. Pearl, J. 2000. Causality: Models, Reasoning, and Inference. Cambridge University Press.