Bridging the Gap Between Evolvable Hardware and Industry Using Cartesian Genetic Programming

cartesian genetic programming, circuit design, scalability problem

Advancements in technology developed in the early nineties have enabledresearchers to successfully apply techniques of evolutionary computation invarious problem domains. As a consequence, a new research direction referred to asevolvable hardware (EHW) focusing on the use of evolutionary algorithms to createspecialized electronics has emerged. One of the goals of the early pioneers of EHWwas to evolve complex circuits and overcome the limits of traditional design. Unfortunately,evolvable hardware found itself in a critical stage around 2010 and a verypessimistic future for EHW-based digital circuit synthesis was predicted. The problemssolved by the community were of the size and complexity of that achievablein fifteens years ago and seldom compete with traditional designs. The scalabilityproblem has been identified as one of the most difficult problems that researchersare faced with and it was not clear whether there existed a path forward that wouldallow the field to progress. Despite that, researchers have continued to investigatehow to overcome the scalability issues and significant progress has been made inthe area of evolutionary synthesis of digital circuits in recent years. The goal ofthis chapter is to summarize the progress in the evolutionary synthesis of gate-leveldigital circuits, and to identify the challenges that need to be addressed to enableevolutionary methods to penetrate into industrial practice.

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• pdf ch2018_cgp.pdf 177 kB