Computing with Bayesian Multi-networks Computing with Bayesian Multi-networks
نویسنده
چکیده
Existing probabilistic approaches to automated reasoning impose severe restrictions on its knowledge representation scheme. Mainly, this is to ensure that there exists an eeective inferencing algorithm. Unfortunately , this makes the application of these approaches to general domains quite diicult. In this paper, we present a new model called Bayesian multi-networks which uses a rule-based organization of knowledge quite natural for human experts modeling various domains. Furthermore, strong probabilistic semantics help quantify the knowledge. Combined with the rich structure of rule-based approaches, a general inference engine for Bayesian multi-networks is developed.
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