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Hill Climbing Beats Genetic Search on a Boolean Circuit Synthesis Problem of Koza's

机译:关于Koza的布尔电路综合问题,爬坡击败了遗传搜索

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摘要

An experiment described in chapter 9 of the book "Genetic Programming" shows that the method is more efficient than random-generate-and-test on a boolean circuit synthesis task. Here we show that hill climbing is more efficient than genetic programming on this problem. It is interesting to note that our improved results were obtained by mating the current best hypothesis with completely random S-expressions, rather than with members of a high-fitness population. Perhaps, for this task, fragments of high fitness individuals have no special value when transplanted into other individuals.
机译:在“遗传编程”一书的第9章中描述的实验表明,该方法比对布尔电路综合任务的随机生成和测试更为有效。在这里,我们证明了在这个问题上爬山比遗传编程更有效。有趣的是,我们的改进结果是通过将当前的最佳假设与完全随机的S表达式而不是与高适应人群的成员相匹配而获得的。也许,对于这项任务,高适应度个体的碎片在移植到其他个体时没有特殊价值。

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