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 ...

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

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 ...

Dr. James McCaffrey of Microsoft Research says that when quantum computing becomes generally available, evolutionary algorithms for training huge neural networks could become a very important and ...

Evolutionary algorithms are an interesting topic of study. Rather then relying on human ingenuity and investigation to create new designs, instead, an algorithm is given a target to achieve, and ...

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 ...

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

Large language models (LLMs) leverage unsupervised learning to capture statistical patterns within vast amounts of text data. At the core of these models lies the Transformer architecture, which ...