Evolving solutions to computational problems using materials

by Julian Miller (University of York)

16:00 (60 min) in CT 7.01

Natural evolution has been manipulating the properties of proteins for billions of years. In the NASCENCE research project we aim to use evolutionary algorithms to manipulate materials to solve computationalproblems. NASCENCE: Nanoscale Engineering of Novel Computation using Evolution is a 2.9M euros EU funded project in Unconventional computation.The aim of the NASCENCE project is to model, understand and exploit the behaviour of evolved configurations ofnanosystems (e.g. networks of nanoparticles, carbon nanotubes, liquid crystals) with the long term goal to buildinformation processing devices exploiting these architectures.

The methodology behind this is called evolution-in-materio (EIM). In EIM, computers running evolutionary algorithmsare used to define configurations and magnitudes of physical variables (e.g. voltages)which are applied to material systems so that they carry out useful computation. One of the potential advantages of this is that artificial evolution can potentially exploit physicaleffects that are either too complex to understand or hitherto unknown.I give an overview of how it is possible to solve a variety of computational problems by using materialsin the genotype-phenotype map used in evolutionary algorithms. Such problems include: TSP, Binpacking, Logic gates, Machine classification, Function optimizationand robot control.