What are genetic algorithms and how did they develop over time?

What are genetic algorithms and how did they develop over time?

Genetic algorithms are optimization techniques inspired by natural selection. They evolved in the 1960s, pioneered by John Holland.

Can you explain how they work in simple terms?

Sure! They mimic the process of natural evolution, using selection, crossover, and mutation to evolve solutions to problems.

What are some real-world applications of genetic algorithms?

They are used in various fields like engineering, economics, and artificial intelligence for optimization problems.

Who are the key figures in the development of genetic algorithms?

Key figures include John Holland, who introduced the concept, and later researchers like David E. Goldberg who expanded on it.

How do genetic algorithms compare to other optimization methods?

They are often more effective for complex problems where traditional methods struggle, but they can be slower to converge.