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No Two Brains Are Alike: Cloning a Hyperdimensional Associative Memory Using Cellular Automata Computations

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Biologically Inspired Cognitive Architectures (BICA) for Young Scientists (BICA 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 636))

Abstract

This paper looks beyond of the current focus of research on biologically inspired cognitive systems and considers the problem of replication of its learned functionality. The considered challenge is to replicate the learned knowledge such that uniqueness of the internal symbolic representations is guaranteed. This article takes a neurological argument “no two brains are alike” and suggests an architecture for mapping a content of the trained associative memory built using principles of hyperdimensional computing and Vector Symbolic Architectures into a new and orthogonal basis of atomic symbols. This is done with the help of computations on cellular automata. The results of this article open a way towards a secure usage of cognitive architectures in a variety of practical application domains.

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Acknowledgements

This study is supported in part by the Swedish Research Council (grant no. 2015-04677). The authors thank Ozgur Yilmaz for fruitful discussions during BICA2016 on the usage of cellular automata in the scope of hyperdimensional computing, which inspired the current work and Niklas Karvonen for general discussions on cellular automata.

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Authors and Affiliations

  1. Luleå University of Technology, 971 87, Luleå, Sweden

    Denis Kleyko & Evgeny Osipov

Authors
  1. Denis Kleyko
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  2. Evgeny Osipov
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Correspondence to Denis Kleyko .

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Editors and Affiliations

  1. Krasnow Institute, George Mason University, Fairfax, VA, USA

    Alexei V. Samsonovich

  2. National Research Nuclear University MEPhI, Moscow, Russia

    Valentin V. Klimov

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Kleyko, D., Osipov, E. (2018). No Two Brains Are Alike: Cloning a Hyperdimensional Associative Memory Using Cellular Automata Computations. In: Samsonovich, A., Klimov, V. (eds) Biologically Inspired Cognitive Architectures (BICA) for Young Scientists. BICA 2017. Advances in Intelligent Systems and Computing, vol 636. Springer, Cham. https://doi.org/10.1007/978-3-319-63940-6_13

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  • DOI: https://doi.org/10.1007/978-3-319-63940-6_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63939-0

  • Online ISBN: 978-3-319-63940-6

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