Chemical Computing Through Simulated Evolution
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InCollection{Bull:2017:miller,
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author = "Larry Bull and Rita Toth and Chris Stone and
Ben {De Lacy Costello} and Andrew Adamatzky",
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title = "Chemical Computing Through Simulated Evolution",
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booktitle = "Inspired by Nature: Essays Presented to Julian F.
Miller on the Occasion of his 60th Birthday",
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publisher = "Springer",
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year = "2017",
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editor = "Susan Stepney and Andrew Adamatzky",
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volume = "28",
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series = "Emergence, Complexity and Computation",
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chapter = "13",
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pages = "269--286",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-319-67996-9",
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DOI = "doi:10.1007/978-3-319-67997-6_13",
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abstract = "Many forms of unconventional computing, i.e.,
massively parallel computers which exploit the
non-linear material properties of their substrate, can
be realised through simulated evolution. That is, the
behaviour of non-linear media can be controlled
automatically and the structural design of the media
optimized through the nature-inspired machine learning
approach. This chapter describes work using the
Belousov-Zhabotinsky reaction as a non-linear chemical
medium in which to realise computation. Firstly,
aspects of the basic structure of an experimental
chemical computer are evolved to implement two Boolean
logic functions through a collision-based scheme.
Secondly, a controller is evolved to dynamically affect
the rich spatio-temporal chemical wave behaviour to
implement three Boolean functions, in both simulation
and experimentation.",
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notes = "part of \cite{miller60book}
https://link.springer.com/bookseries/10624",
- }
Genetic Programming entries for
Larry Bull
Rita Toth
Chris Stone
Ben De Lacy Costello
Andrew Adamatzky
Citations