遺傳算法（Genetic Algorithms，GAs）是進(jìn)化計(jì)算中的重要領(lǐng)域，也是人工智能迅速發(fā)展的重要領(lǐng)域，它是一類模擬自然進(jìn)化過程和達(dá)爾文“適者生存”的算法。這一算法企圖通過使用諸如交叉、變異等算子從先前的候選解中生成最佳解。進(jìn)化硬件（Evolvable Hardware，EHW）則是受自然進(jìn)化得到靈感、設(shè)計(jì)硬件系統(tǒng)的新型設(shè)計(jì)方法，它是進(jìn)化計(jì)算技術(shù)和電子硬件結(jié)合的產(chǎn)物。本文給出GAs在計(jì)算機(jī)模型中的基本概念，討論進(jìn)化再配置硬件的設(shè)計(jì)，最后給出幾個(gè)進(jìn)化實(shí)驗(yàn)的例子。
關(guān)鍵詞 遺傳算法 進(jìn)化硬件 進(jìn)化實(shí)驗(yàn)
Abstract Genetic algorithms are an important area of Evolutionary Computing, which is a rapidly growing area of Artificial Intelligence. They are a class of algorithms which mimic the natural process of Evolution and Darwin’s principle of "Survival of the Fittest", The algorithms attempt to generate the best solution from previous solutions by the use of genetic operators such as crossover & mutation. Evolvable Hardware is a new scheme inspired by natural evolution, for designing hardware systems. It is also a child of the marriage between evolutionary computation techniques and electronic hardware. The paper presents basic concepts of Genetic Algorithm in its computer model and discusses design of evolvable reconfigurable hardware. Finally, some examples in evolutionary experiments are presented.
Keywords Genetic algorithms；Evolvable hardware；Evolutionary experiments