As evolution can produce highly optimized processes and networks, it has many applications in [[computer science]]. Here, simulations of evolution using [[evolutionary algorithm]]s and [[artificial life]] started with the work of Nils Aall Barricelli in the 1960s, and was extended by [[Alex Fraser (scientist)|Alex Fraser]], who published a series of papers on simulation of [[artificial selection]]. [[Artificial evolution]] became a widely recognized optimization method as a result of the work of [[Ingo Rechenberg]] in the 1960s and early 1970s, who used [[evolution strategies]] to solve complex engineering problems. [[Genetic algorithms]] in particular became popular through the writing of [[John Henry Holland|John Holland]]. As academic interest grew, dramatic increases in the power of computers allowed practical applications. Evolutionary algorithms are now used to solve multi-dimensional problems more efficiently than software produced by human designers, and also to optimize the design of systems. | As evolution can produce highly optimized processes and networks, it has many applications in [[computer science]]. Here, simulations of evolution using [[evolutionary algorithm]]s and [[artificial life]] started with the work of Nils Aall Barricelli in the 1960s, and was extended by [[Alex Fraser (scientist)|Alex Fraser]], who published a series of papers on simulation of [[artificial selection]]. [[Artificial evolution]] became a widely recognized optimization method as a result of the work of [[Ingo Rechenberg]] in the 1960s and early 1970s, who used [[evolution strategies]] to solve complex engineering problems. [[Genetic algorithms]] in particular became popular through the writing of [[John Henry Holland|John Holland]]. As academic interest grew, dramatic increases in the power of computers allowed practical applications. Evolutionary algorithms are now used to solve multi-dimensional problems more efficiently than software produced by human designers, and also to optimize the design of systems. |