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Embedding Vector Differences Can Be Aligned with Uncertain Intensional Logic Differences

机译:嵌入的矢量差异可以与不确定的内涵逻辑差异对齐

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The DeepWalk algorithm is used to assign embedding vectors to nodes in the Atomspace weighted, labeled hypergraph that is used to represent knowledge in the OpenCog AGI system, in the context of an application to probabilistic inference regarding the causes of longevity based on data from biological ontologies and genomic analyses. It is shown that vector difference operations between embedding vectors are, in appropriate conditions, approximately alignable with "intensional difference" operations between the hypergraph nodes corresponding to the embedding vectors. This relationship hints at a broader functorial mapping between uncertain intensional logic and vector arithmetic, and opens the door for using embedding vector algebra to guide intensional inference control.
机译:DeepWalk算法用于将嵌入向量分配给Atomspace加权的,带标签的超图中的节点,该超图用于表示OpenCog AGI系统中的知识,这是基于生物学本体数据对寿命原因进行概率推断的应用和基因组分析。结果表明,在适当的条件下,嵌入向量之间的向量差运算可以与对应于嵌入向量的超图节点之间的“内涵差”运算近似对齐。这种关系暗示了不确定的内涵逻辑和矢量算术之间的函数映射更广泛,并为使用嵌入矢量代数指导内涵推理控制打开了大门。

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