Evolution-in-materio: Solving function optimization problems using materials

Evolution-in-materio (EIM) is a method that uses artificial evolution to exploit properties of materials to solve computational problems without requiring a detailed understanding of such properties. In this paper, we show that using a purpose-built hardware platform called Mecobo, it is possible to...

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Bibliographic Details
Published inUK Workshop on Computational Intelligence pp. 1 - 8
Main Authors Mohid, Maktuba, Miller, Julian F., Harding, Simon L., Tufte, Gunnar, Lykkebo, Odd Rune, Massey, Mark K., Petty, Michael C.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2014
Subjects
Arrays
Benchmark testing
Biological cells
Electrodes
evolution-in-materio
evolutionary algorithm
evolvable hardware
function optimization
Hardware
material computation
Materials
Optimization
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ISSN2162-7657
DOI10.1109/UKCI.2014.6930152

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Summary:Evolution-in-materio (EIM) is a method that uses artificial evolution to exploit properties of materials to solve computational problems without requiring a detailed understanding of such properties. In this paper, we show that using a purpose-built hardware platform called Mecobo, it is possible to evolve voltages and signals applied to physical materials to solve computational problems. We demonstrate for the first time that this methodology can be applied to function optimization. We evaluate the approach on 23 function optimization benchmarks and in some cases results come very close to the global optimum or even surpass those provided by a well-known software-based evolutionary approach. This indicates that EIM has promise and further investigations would be fruitful.
ISSN:2162-7657
DOI:10.1109/UKCI.2014.6930152