A Learning Method for Dynamic Bayesian Network Structures Using a Multi-Objective Particle Swarm Optimizer

被引：0

作者：

Shibata, Kousuke ^{[1
]}

Nakano, Hidehiro ^{[1
]}

Miyauti, Arata ^{[1
]}

机构：

[1] Tokyo City Univ, Setagay Ku, 1-28-1 Tamadutsumi, Tokyo 1588557, Japan

来源：

PROCEEDINGS OF THE SIXTEENTH INTERNATIONAL SYMPOSIUM ON ARTIFICIAL LIFE AND ROBOTICS (AROB 16TH '11) | 2011年

关键词：

Dynamic Bayesian Networks; Structure Learning; Multi-Objective Optimization; Discrete Particle Swarm Optimization;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we present a multi-objective Discrete Particle Optimizer (DPSO) for the learning of 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 find effective DBN sub-network structures and a group of MOGA finds whole of the DBN network structure. Through numerical simulations, the proposed method can find more effective DBN structures and can obtain them faster than the conventional method.

引用

页码：877 / 880

页数：4

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