A demonstration of vector symbolic architecture as an effective integrated technology for AI at the network edge

Vector Symbolic Architecture (VSA), a.k.a. Hyperdimensional Computing has transformative potential for advancing cognitive processing capabilities at the network edge. This paper presents a technology integration experiment, demonstrating how the VSA paradigm offers robust solutions for generation-after-next AI deployment at the network edge. Specifically, we show how VSA effectively models and integrates the cognitive processes required to perform intelligence, surveillance, and reconnaissance (ISR). The experiment integrates functions across the observe, orientate, decide and act (OODA) loop, including the processing of sensed data via both a neuromorphic event-based camera and a standard CMOS frame-rate camera; declarative knowledge-based reasoning in a semantic vector space; action planning using VSA cognitive maps; access to procedural knowledge via large language models (LLMs); and efficient communication between agents via highly-compact binary vector representations. In contrast to previous ‘point solutions’ showing the effectiveness of VSA for individual OODA tasks, this work takes a ‘whole system’ approach, demonstrating the power of VSA as a uniform integration technology.

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Published
2024-11-13
DOI
https://doi.org/10.1117/12.3030952
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

A demonstration of vector symbolic architecture as an effective integrated technology for AI at the network edge

Alun D. Preece, Gaetano Di Caterina, Marc Roig Vilamala, Paul Kirkland et al.
Neural Networks and Applications
article

A demonstration of vector symbolic architecture as an effective integrated technology for AI at the network edge

Alun D. Preece, Gaetano Di Caterina, Marc Roig Vilamala, Paul Kirkland, Cai Davies, Gavin Pearson, Graham Bent, Alex Vicente Sola, B. Tutcher, Yuhua Li
article en

Abstract

Vector Symbolic Architecture (VSA), a.k.a. Hyperdimensional Computing has transformative potential for advancing cognitive processing capabilities at the network edge. This paper presents a technology integration experiment, demonstrating how the VSA paradigm offers robust solutions for generation-after-next AI deployment at the network edge. Specifically, we show how VSA effectively models and integrates the cognitive processes required to perform intelligence, surveillance, and reconnaissance (ISR). The experiment integrates functions across the observe, orientate, decide and act (OODA) loop, including the processing of sensed data via both a neuromorphic event-based camera and a standard CMOS frame-rate camera; declarative knowledge-based reasoning in a semantic vector space; action planning using VSA cognitive maps; access to procedural knowledge via large language models (LLMs); and efficient communication between agents via highly-compact binary vector representations. In contrast to previous ‘point solutions’ showing the effectiveness of VSA for individual OODA tasks, this work takes a ‘whole system’ approach, demonstrating the power of VSA as a uniform integration technology.

Defence Science and Technology Laboratory (GB), University of Strathclyde (GB), Cardiff University (GB)
Defence Science and Technology Laboratory
Openalex Percentile: Top 82%
Neural Networks and Applications
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A demonstration of vector symbolic architecture as an effective integrated technology for AI at the network edge — Alun D. Preece, Gaetano Di Caterina, et al. · (2024) | TGRS Research Map | TGRS