中文说明:在人工智能领域,遗传算法 (GA) 是搜索的启发式算法,模仿自然选择的过程。这种试探法 (有时也称为超启发式) 经常用于生成有用的解决方案,优化和搜索问题。[1] 遗传算法属于进化算法 (EA) 生成使用技术灵感来自自然的演变,如继承、 交叉、 变异、 选择、 优化问题的解决办法的大类。下面是代码为短的路。
English Description:
In the field of artificial intelligence, a genetic algorithm (GA) is a search heuristic that mimics the process of natural selection. This heuristic (also sometimes called a metaheuristic) is routinely used to generate useful solutions to optimization and search problems.[1] Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover. Here is the code for short road.