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电子学报  2006 

基于遗传与粒子群算法的Markov逻辑网学习研究

, PP. 2551-2555

Keywords: 统计关系学习,Markov逻辑网,谓词模板,子句模板,遗传算法,粒子群算法

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Abstract:

Markov逻辑网(MLN)是一种重要的统计关系模型,目前其学习问题主要采用确定性的优化方法,所求的解不够简洁、易陷入局部极值.针对这些问题,本文定义谓词模板、子句模板以缩小搜索空间,提出一种采用子句模板编码的遗传算法来学习MLN结构,并用粒子群算法学习MLN的权参数.文中设计了适应度函数和相应的遗传算子,保证算法不断向好的逻辑子句结构进化.理论分析与实验结果都表明本文的算法可以学习到较优解.

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