Evolutionary computation comprises a family of metaheuristic algorithms inspired by the principles of natural evolution – reproduction, mutation, recombination, and selection – which are utilised to ...

Evolutionary computation (EC) incorporates evolutionary ideas into algorithms. These algorithms can be applied to problems of biological interest. They are interesting models for evolution, so that EC ...

Assistant Professor Robert MacCurdy and his collaborators have won the ACM SIGEVO Impact Award for their outstanding contributions in the field of genetic and evolutionary computation. The award ...

This course will guide students on their own intellectual journey in evolutionary computation. Early lectures provide a jumping off point — an overview of genetic algorithms, evolutionary strategies, ...

Constantly "re-rolling the dice", combining and selecting: "Evolutionary algorithms" mimic natural evolution in silico and lead to innovative solutions for complex problems. Constantly “re-rolling the ...

It turns out that 155 years after Charles Darwin first published “On the Origin of Species,” vexing questions remain about key aspects of evolution, such as how sexual recombination and natural ...

Immigration is generally considered an option in genetic algorithms, but I have found immigration to be extremely useful in almost all situations where I use evolutionary optimization. The idea of ...

For over a thousand years, the story of human evolution was simple: Homo sapiens developed in Africa between 200,000 and 300,000 years ago from a single line of forebears. But today, one research has ...