This paper presents the development of a low-SWaP spiking symbolic Bayesian network reasoner that makes decisions based on given state inputs. The Bayesian network is demonstrated onboard an unmanned aerial vehicle using the Intel Loihi, a neuromorphic research hardware, and achieves improved power efficiency, runtime performance, and functional equivalency when compared to conventional hardware.


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    Title :

    Symbolic Probabilistic Cognitive Reasoner on Neuromorphic Hardware


    Contributors:
    Fan, David (author) / DeMange, Ashley (author) / Jenkins, Todd (author) / Adams, Yuki (author) / Taha, Tarek (author)


    Publication date :

    2021-08-16


    Size :

    1773823 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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