روش مبتنی بر محاسبات جدید تکاملی برای آموزش های بیزی شبکه

Bayesian network is a popular tool for uncertainty process in Artificial Intelligence. In recent years, more and more attention has been paid to learning of Bayesian network. In this paper, we proposed a novel learning algorithm for Bayesian network based on (μ, λ)-Evolution Strategy, we present the encoding scheme and fitness function, designed the evolutionary operators of recombination, mutation and selection. Theoretical analysis and experimental results all demonstrate that the proposed method can learn the Bayesian network from data effectively.