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Embedding Vector Differences Can Be Aligned with Uncertain Intensional Logic Differences

Authors :
Mike Duncan
Man Hin Leung
Debbie Duong
Matthew Iklé
Hedra Seid
Abdulrahman Semrie
Ben Goertzel
Nil Geisweiller
Source :
Artificial General Intelligence ISBN: 9783030521516, AGI
Publication Year :
2020
Publisher :
Springer International Publishing, 2020.

Abstract

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.

Details

ISBN :
978-3-030-52151-6
ISBNs :
9783030521516
Database :
OpenAIRE
Journal :
Artificial General Intelligence ISBN: 9783030521516, AGI
Accession number :
edsair.doi...........712afabb76aeff42d7e1955dbc0c630b