Answering queries in hybrid Bayesian networks using importance sampling
Identificadores
URI: http://hdl.handle.net/10835/4895
DOI: https://doi.org/10.1016/j.dss.2012.03.007
DOI: https://doi.org/10.1016/j.dss.2012.03.007
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2012Resumen
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.
Palabra/s clave
Bayesian networks
Probabilistic reasoning
Importance sampling
Mixtures of truncated exponentials