The intersection of evolutionary algorithms and data-driven optimisation is reshaping materials science by offering novel computational frameworks for designing and refining materials. Drawing ...

Evolutionary algorithms (EAs) represent a class of heuristic optimisation methods inspired by natural selection and Mendelian genetics. They iteratively evolve a population of candidate solutions ...

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 ...

Evolutionary Algorithms are a family of optimisation algorithms inspired by the process of natural selection. They are used to solve complex optimisation problems in various fields, such as ...

Artificial intelligence and machine learning are becoming more and more relevant in everyday life – and the same goes for chemistry. Organic chemists, for example, are interested in how machine ...

Evolutionary reinforcement learning is an exciting frontier in machine learning, combining the strengths of two distinct approaches: reinforcement learning and evolutionary computation. In ...

A team led by Prof Frank Glorius from the Institute of Organic Chemistry at the University of Münster has developed an evolutionary algorithm that identifies the structures in a molecule that are ...

In the diverse world of Artificial Intelligence (AI), Genetic Algorithms (GAs) are a search heuristic that are inspired by Charles Darwin's theory of natural evolution. This evolutionary algorithm ...