Reinforcement learning with actor-critic for knowledge graph reasoning

被引：1
|
作者：
Linli ZHANG [1 ,2 ]
Dewei LI [1 ,2 ]
Yugeng XI [1 ,2 ]
Shuai JIA [1 ,2 ]
机构：
[1] Department of Automation, Shanghai Jiao Tong University
来源：
Science China(Information Sciences) | 2020年 / 63卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Reinforcement learning with actor-critic for knowledge graph reasoning; MDP;
D O I：
暂无
中图分类号：
TP181 [自动推理、机器学习]; TP391.1 [文字信息处理];
学科分类号：
摘要：
Dear editor,In recent years, with the development of artificial intelligence and deep learning techniques, knowledge graph (KG) is receiving unprecedented attention. Essentially, KG is a semantic network, which stores massive information structured as entityrelation pairs in a graphical model. When the keywords or questions that users input are mapped
引用
收藏
页码：223 / 225
页数：3
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