Cartesian Genetic Programming (CGP) is a well-known form of Genetic Programming
developed by Julian Miller in 1999-2000. In its classic form, it uses a very simple integer …

Cartesian genetic programming, a well-established method of genetic programming, is
approximately 20 years old. It represents solutions to computational problems as graphs. Its …

In approximate computing, the requirement of perfect functional behavior can be relaxed
because some applications are inherently error resilient. Approximate circuits, which fall into …

Technology scaling poses an increasing challenge to the reliability of digital circuits.
Hardware redundancy solutions, such as triple modular redundancy (TMR), produce very …

In the last decade, the research community has been actively working to develop the
techniques that can automatically find a solution to a software fault, namely, automatic …

Recently, power efficiency has become the most important parameter of many real circuits.
At the same time, a wide range of applications capable of tolerating imperfections has …

A new approach to the evolutionary optimization of large digital circuits is introduced in this
paper. In contrast with evolutionary circuit design, the goal of the evolutionary circuit …

Reversible computing has gained increasing attention as a prospective solution for energy
dissipation, particularly in quantum computing. As the first practical reversible logic gate …

Functional approximation is one of the methods allowing designers to approximate circuits
at the level of logic behavior. By introducing a suitable functional approximation, power …

Advancements in technology developed in the early nineties have enabled researchers to
successfully apply techniques of evolutionary computation in various problem domains. As a …