Structure Learning of Belief Network by Genetic Algorithms: A New Network Encoding Method
Cong Zhang, Shen Yi · 2004
In the last few years Belief networks have become a popular way of modeling probabilistic relationships among a set of variables for a given domain. It's a very hard task that treats a good belief network for large domains. Therefore, some researchers have studied how this construction can be automated. This work introduces how to do structure learning by genetic algorithms and discuss the encoding method using in GA. A new encoding method has presented. A case study has shown that GA is good for structure learning.