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Evolutionary- and Quantum-Inspired Computation. Applications for SNN Optimisation

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Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence

Part of the book series: Springer Series on Bio- and Neurosystems ((SSBN,volume 7))

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Abstract

The chapter introduces the main principles and several algorithms of both evolutionary computation (EC) and its further development as quantum inspired evolutionary computation (QiEC).

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Acknowledgements

The chapter includes some materials published previously by the author in collaboration with colleagues. I acknowledge the contribution of the following colleagues in these publications: Stefan Schliebs, Haza Nuzly, Michael Defoin-Platel, Mike Watts. Some of the material is also taken from my previous books with Springer [44, 62, 64].

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Authors and Affiliations

  1. Knowledge Engineering and Discovery Research Institute (KEDRI), Auckland University of Technology, Auckland, New Zealand

    Nikola K. Kasabov

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  1. Nikola K. Kasabov
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Correspondence to Nikola K. Kasabov .

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Kasabov, N.K. (2019). Evolutionary- and Quantum-Inspired Computation. Applications for SNN Optimisation. In: Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence . Springer Series on Bio- and Neurosystems, vol 7. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-57715-8_7

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