Propositional Deductive Inference by Semantic Vectors

被引：0
|
作者：
Summers-Stay, Douglas [1 ]
机构：
[1] US Army Res Lab, 2800 Powder Mill Rd, Adelphi, MD 20783 USA
来源：
INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 1 | 2020年 / 1037卷
关键词：
Semantic vectors; Deductive inference; Propositional logic;
D O I：
10.1007/978-3-030-29516-5_61
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Representing symbols by high-dimensional vectors makes it easier to perform analogical and associational reasoning, but performing multi-step deductive reasoning typically requires a discrete knowledge base. In this paper, we show a method by which deductive inference can be performed directly on high-dimensional semantic vectors, and characterize some limitations and advantages of this approach. We provide a method for taking a set of semantic vectors representing propositions and encoding a knowledge base telling how those propositions are logically related.
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页码：810 / 820
页数：11
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