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

At the intersection of neuroscience and artificial intelligence (AI) is an alternative approach to deep learning. Evolutionary algorithms (EA) are a subset of evolutionary computation—algorithms that ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More The promise of evolutionary algorithms has been around for several years, ...

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, ...

A professor recently developed an evolutionary computation approach that offers researchers the flexibility to search for models that can best explain experimental data derived from many types of ...

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 ...

At the intersection of neuroscience and artificial intelligence (AI) is an alternative approach to deep learning. Evolutionary algorithms (EA) are a subset of evolutionary computation—algorithms that ...

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 ...

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 ...

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 ...