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Imitation Programming Unorganised Machines

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Artificial Intelligence, Evolutionary Computing and Metaheuristics

Part of the book series: Studies in Computational Intelligence ((SCI,volume 427))

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Abstract

In 1948 Alan Turing presented a general representation scheme by which to achieve artificial intelligence – his unorganised machines. Further, at the same time as also suggesting that natural evolution may provide inspiration for search, he noted that mechanisms inspired by the cultural aspects of learning may prove useful. This chapter presents results from an investigation into using Turing’s dynamical network representation designed by a new imitation-based, i.e., cultural, approach. Moreover, the original synchronous and an asynchronous form of unorganised machines are considered, along with their implementation in memristive hardware.

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Authors and Affiliations

  1. Department of Computer Science & Creative Technologies, University of the West of England, Bristol, BS16 1QY, U.K

    Larry Bull

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  1. Larry Bull
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Correspondence to Larry Bull .

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  1. , Mathematics and Scientific Computing, National Physical Laboratory, Hampton Road, Teddington, TW11 0LW, United Kingdom

    Xin-She Yang

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Bull, L. (2013). Imitation Programming Unorganised Machines. In: Yang, XS. (eds) Artificial Intelligence, Evolutionary Computing and Metaheuristics. Studies in Computational Intelligence, vol 427. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29694-9_4

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  • DOI: https://doi.org/10.1007/978-3-642-29694-9_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29693-2

  • Online ISBN: 978-3-642-29694-9

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