Hands-On Genetic Algorithms with Python by Eyal Wirsansky is a new book which explores the world of genetic algorithms to solve search, optimization, and AI-related tasks, and improve machine ...

The approach combines a new genetic algorithm using empirical interatomic potentials to explore the configurational phase space of boundaries, and thereafter refining structures and free energies ...

Typically, standard genetic algorithms use a form of bit representation, while evolutionary algorithms use real values, but this vocabulary distinction is arbitrary.

The considered optimization problem is NP-hard, that is why we proposed a two-level based genetic algorithm in order to solve it. The computational results reported on a set of existing benchmark ...

By analyzing thousands of genetic risk variants, a new algorithm may be able to predict your risk of developing chronic kidney disease decades before onset.

The MMRDetect clinical algorithm makes it possible to identify tumours that have 'mismatch repair deficiencies' and then improve the personalisation of cancer therapies to exploit those weaknesses.