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 ...

Evolutionary principles were already being presented as a possibly viable approach to computational methods as early as the 1950s; however, evolutionary algorithms are yet to have their big moment.

Game theory has been applied to evolutionary theory before, to study the evolution of strategic individual behavior (see, e.g., refs. 6, 7).The connection between game theory and evolution that we ...

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 ...

Because evolutionary algorithms use random operations for crossover and mutation, the Solver class uses a Random object member rather than relying on a global Random object. The pop (population) ...

Abstract: Evolutionary algorithm is a kind of according to the selection and evolution of biological evolution model and the evolution of a kind of random search technology. Evolutionary algorithm is ...

When using an evolutionary algorithm you need to define a method for the specific problem being optimized. In some situations you might need to pass additional information to the Solver class. For ...