In this article, we present a multi-objective discrete particle swarm optimizer (DPSO) for learning dynamic Bayesian network (DBN) structures. The proposed method introduces a hierarchical structure consisting of DPSOs and a multi-objective genetic algorithm (MOGA). Groups of DPSOs fi nd effective DBN sub-network structures and a group of MOGAs fi nd the whole of the DBN network structure. Through numerical simulations, the proposed method can fi nd more effective DBN structures, and can obtain them faster than the conventional method.

No abstract