a new approach for structurallearning in bayesian networks based on local best PSO

learning bayesian networks BNs form data is a NP-hard problem. Therfore most score-based learning methods work with a heuristic search we could consider the problem of structural learning of BNs as an optimization problem and solve it by a PSO algorithm which is a nature-inspired population based stochastic search technique . this paper describes a method for finding the highest scoring structure among all possible structures of a bayesian network based on local best versionof the PSO algorithm the results of experiments show that the proposed algorithm outperforms the standard PSO algorithm in the structural learning BN problem

Keywords:

bayesian networks , structural learning , particle swarm optimization