Integrating Semantic Annotations in Bayesian Causal Models
نویسندگان
چکیده
Probabilistic reasoning has been powered by the formalization of causality theory through Bayesian causal models[1]. Even when its semantic is flexible enough to model complex problems, it has to deal with the problem of interoperability between models. In the research community the necessity of contexts for these models has been pointed out. We need means to represent the context on which the causal model is developed and the meaning of causal model events in the real world.
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