Estimation of distribution programming based on Bayesian network
Estimation of distribution programming based on Bayesian network
复制标题
基于贝叶斯网络的分布规划估计
DOI：
10.1109/cec.2003.1299866
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发表时间：
2003
期刊：
影响因子：
--
通讯作者：
H. Iba
中科院分区：
文献类型：
--
作者：
Kohsuke Yanai;H. Iba
我们提出基于使用贝叶斯网络的概率分布表达式的分布规划（EDP）估计。 EDP是一种基于群体的程序搜索方法，其中估计群体概率分布，并根据结果生成个体。我们关注程序节点（表示为树结构）的依赖关系是明确的这一事实，并使用贝叶斯网络估计程序总体的概率分布。我们在几个基准测试（即最大值问题和布尔函数问题）上将 EDP 与 GP（遗传编程）进行比较。我们还讨论了 EDP 的强项问题的趋势。
We propose estimation of distribution programming (EDP) based on a probability distribution expression using a Bayesian network. EDP is a population-based program search method, in which the population probability distribution is estimated, and individuals are generated based on the results. We focus our attention on the fact that the dependency relationship of nodes of the program (expressed as a tree structure) is explicit, and estimate the probability distribution of the program population using a Bayesian network. We compare EDP with GP (genetic programming) on several benchmark tests, i.e., a max problem and a Boolean function problem. We also discuss the trends of problems that are the forte of EDP.