Propagating imprecise probabilities in Bayesian networks
نویسندگان
چکیده
منابع مشابه
Propagating Imprecise Probabilities in Bayesian Networks
Often experts are incapable of providingèxact' probabilities; likewise, samples on which the probabilities in networks are based must often be small and preliminary. In such cases the probabilities in the networks are imprecise. The imprecision can be handled by second-order probability distributions. It is convenient to use beta or Dirichlet distributions to express the uncertainty about proba...
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In this paper we suggest a way of using the rules of System P to propagate lower bounds on conditional probabilities. Using a knowledge base of default rules which are considered to be constraints on a probability distribution, the result of applying the rules of P gives us new constraints that were implicit in the knowledge base and their associated lower bounds.
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ژورنال
عنوان ژورنال: Artificial Intelligence
سال: 1996
ISSN: 0004-3702
DOI: 10.1016/s0004-3702(96)00021-5