Answering queries in hybrid Bayesian networks using importance sampling

作者：Fernandez Antonio^*; Rumi Rafael; Salmeron Antonio

来源：Decision Support Systems, 2012, 53(3): 580-590.

DOI：10.1016/j.dss.2012.03.007

• Bayesian networks
• Probabilistic reasoning
• Importance sampling
• Mixtures of truncated exponentials

In this paper we propose an algorithm for answering queries in hybrid Bayesian networks where the underlying probability distribution is of class MTE (mixture of truncated exponentials). The algorithm is based on importance sampling simulation. We show how, like existing importance sampling algorithms for discrete networks, it is able to provide answers to multiple queries simultaneously using a single sample. The behaviour of the new algorithm is experimentally tested and compared with previous methods existing in the literature.

• 出版日期2012-6