Ziegler等通过以节点为单位分解评分函数,从而改进了贪婪算法的搜索策略,提高了算法的精度。(Approximation algorithms for restricted Bayesian network structures)
Campos等然提出了基于蚁群优化算法的贝叶斯网络结构学习(Ant colony optimization for learning Bayesian networks)
其他的搜索优化方法,包括贪婪算法,粒子群优化算法,遗传算法,人工蜂群算法等(An artificial bee colony algorithm for learning Bayesian networks\ A Bayesian network learning algorithm based on independence test and ant colony optimization\Bayesian network structure learning algorithm based on ant colony optimization search optimal node ordering)