👉 Genetic computing is a subfield of artificial intelligence that draws inspiration from biological evolution to solve complex computational problems. It mimics the process of natural selection by using algorithms based on principles of genetics, such as mutation, crossover (recombination), and selection. In this approach, potential solutions to a problem are represented as "chromosomes," and a population of these chromosomes undergoes iterative cycles of evaluation, reproduction, and mutation. The fittest solutions, those that perform best according to a predefined fitness function, are selected to produce the next generation of solutions. Over time, this process evolves increasingly effective solutions to the problem at hand, making genetic computing a powerful tool for optimization and search problems where traditional algorithms may struggle.
