Causality in Bayesian belief networks Export

@inproceedings{citeulike:3040213, abstract = {We address the problem of causal interpretation of the graphical structure of Bayesian belief networks (BBNs). We review the concept of causality explicated in the domain of structural equations models and show that it is applicable to BBNs. In this view, which we call mechanism-based, causality is defined within models and causal asymmetries arise when mechanisms are placed in the context of a system. We lay the link between structural equations models and BBNs models and formulate the...}, author = {Druzdzel, M. and Simon, H.}, booktitle = {Proceedings of Ninth Conference on Uncertainty in Artificial Intelligence, \rm Washington, {DC}}, citeulike-article-id = {3040213}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.55.8407}, keywords = {bayesian-networks, causality}, pages = {3--11}, posted-at = {2008-12-09 23:30:58}, priority = {2}, publisher = {Morgan Kaufmann}, title = {Causality in Bayesian belief networks}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.55.8407}, year = {1993} }

TY - CONF ID - citeulike:3040213 L3 - citeulike-article-id:3040213 N2 - We address the problem of causal interpretation of the graphical structure of Bayesian belief networks (BBNs). We review the concept of causality explicated in the domain of structural equations models and show that it is applicable to BBNs. In this view, which we call mechanism-based, causality is defined within models and causal asymmetries arise when mechanisms are placed in the context of a system. We lay the link between structural equations models and BBNs models and formulate the... EP - 11 TI - Causality in Bayesian belief networks PB - Morgan Kaufmann T2 - Proceedings of Ninth Conference on Uncertainty in Artificial Intelligence, \rm Washington, {DC} SP - 3 KW - bayesian-networks KW - causality AU - Druzdzel, M AU - Simon, H PY - 1993/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.55.8407 ER -