Evolutionary Computation

Evolutionary Computation is a method of solving complex problems by mimicking natural selection. It starts with a diverse set of possible solutions, called a population. These solutions are evaluated based on a goal or fitness criteria. The best solutions are selected to produce new ones through processes similar to mutation and crossover, creating a new generation. Over successive generations, the solutions evolve, gradually improving the fit to the problem. This approach is useful for optimization tasks where traditional methods struggle, leveraging principles inspired by biological evolution to find effective, innovative solutions efficiently.