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Towards Intelligently Designed Evolvable Processors

机译：Towards Intelligently Designed Evolvable Processors

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Evolution-in-Materio is a computational paradigm in which an algorithm reconfiguresa material’s properties to achieve a specific computational function. This article addressesthe question of how successful and well performing Evolution-in-Materio processorscan be designed through the selection of nanomaterials and an evolutionaryalgorithm for a target application.Aphysical model of a nanomaterial network is developedwhich allows for both randomness, and the possibility of Ohmic and non-Ohmicconduction, that are characteristic of such materials. These differing networks are thenexploited by differential evolution, which optimises several configuration parameters(e.g., configuration voltages, weights, etc.), to solve different classification problems.We show that ideal nanomaterial choice depends upon problem complexity, withmorecomplex problems being favoured by complex voltage dependence of conductivity andvice versa. Furthermore, we highlight how intrinsic nanomaterial electrical propertiescan be exploited by differing configuration parameters, clarifying the role and limitationsof these techniques. These findings provide guidance for the rational design ofnanomaterials and algorithms for future Evolution-in-Materio processors.

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