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 ...

Genetic algorithms borrow their name and principles from biological evolution, but can they help researchers discover the fundamentals of life? Evolution is one of the most widely known theories in ...

Expensive optimization problem (EOP) refers to the problem that requires expensive or even unaffordable costs to evaluate candidate solutions, which widely exist in many significant real-world ...

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, ...

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 ...