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机构地区:[1]海南五指山市琼州大学,572200
出 处:《微计算机信息》2004年第2期28-30,共3页Control & Automation
基 金:海南省教育厅自然科学基金资助项目 批准号:Hjkj200327
摘 要:遗传算法(Genetic Algorithms,GAs)是进化计算中的重要领域,也是人工智能迅速发展的重要领域,它是一类模拟自然进化过程和达尔文“适者生存”的算法。这一算法企图通过使用诸如交叉、变异等算子从先前的候选解中生成最佳解。进化硬件(Evolvable Hardware,EHW)则是受自然进化得到灵感、设计硬件系统的新型设计方法,它是进化计算技术和电子硬件结合的产物。本文给出GAs在计算机模型中的基本概念,讨论进化再配置硬件的设计,最后给出几个进化实验的例子。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.
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