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蚂蚁算法是拉马克检索的一种形式。Ant algorithms are a type of Lamarckian search.

要获得拉马克生物学还需要别的什么？What else would it take to have a Lamarckian biology?

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传播，与文化学习一样，是拉马克检索的一部分。Broadcasting, like cultural teaching, is a part of Lamarckian search.

不过，拉马克进化需要生物给它的基因下工作指标。But Lamarckian evolution requires an organism to have a working index to its genes.

最聪明的拉马克个体比最聪明的达尔文个体聪明得多。The smartest Lamarckian individual was far smarter than the smartest Darwinian one.

从数学意义上来说，拉马克进化在培养基里注入了一点学习的要素。In a mathematical sense, Lamarckian evolution injects a bit of learning into the soup.

最终，智力萌芽，拉马克的文明进化取而代之。Eventually, when intelligence came on the scene, Lamarckian cultural evolution took over.

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阿克里和利特曼的展示已经表明，由人类编程的计算机能运行拉马克式进化。Ackley and Littman showed that computers programmed by humans could run Lamarckian evolution.

艾克利和利特曼在一台拥有16，000个处理器的计算机上运行了拉马克系统。Ackley and Littman implemented a Lamarckian system on a parallel computer with 16,000 processors.

动物能作出反应，做选择、迁移、适应，为假想的拉马克式进化的兴旺盛行腾出位置。Animals could react, choose, migrate, adapt, and give room for the blossoming of pseudo- Lamarckian evolution.

我的更重要的观点是说，由于拉马克式进化的优势如此显著，因而使自然找到了令其发生的方式。My larger point is that the advantages of Lamarckian evolution are so great that nature has found ways to make it happen.

但近几年，拉马克理论随着科学家对表观遗传学认识的深入有回归的迹象。But the concept of Lamarckian inheritance has made a comeback in recent years, as scientists learn more about epigenetics.

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随着人脑的演化，他们创造出了文化，文化又允许遗传所得的真正的拉马克系统诞生。As human brains evolved, they created culture, which permitted the birth of a true Lamarckian system of inherited acquisitions.

不过，宇宙仍然充满了奇特的潜在算法，都可能利用各种各样的拉马克传播形式。But there remains a universe full of strange types of potential computation that might employ various modes of Lamarckian broadcasting.

它搜寻着拉马克进化的优势而不自知，因为拉马克进化是缺乏抗病性，更多可进化性的一个尝试。It searches for the advantages of Lamarckian evolution without realizing it because Lamarckism is a crack of less resistance and more evolvability.

另一方面，费奇仍主张这些发现虽然是“拉马克式的现象，实际上仍符合达尔文理论，因为这些变化无法永久不灭。”Feig, on the other hand, argues that while the findings are "a Lamarckian kind of phenomenon it's still Darwinian, because the changes don't last forever."

在丰富的复杂性足以产生智能的地方，如在人类有机体和人类组织中，在他们的机器人后代中，拉马克进化不仅可能，而且是有优势的。But where complexity is rich enough for intelligence, such as in human organisms and organizations, and their robotic offspring, Lamarckian evolution is possible and advantageous.

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如果大自然在有机体内真的是双向传递信息的，就会产生拉马克式进化的可能，即需要在基因和基因产物之间双向交流。If nature transmitted information in both directions within organisms , it would allow the possibility of Lamarckian evolution, which requires two-way communication between gene and its products.

经过对两个系统的比较，艾克利和利特曼发现，至少对他们考虑的复杂的问题而言，拉马克系统发现的解决方案比达尔文系统多两倍。Comparing the two systems, Ackley and Littman found that, at least for the complicated problems they looked at, the Lamarckian system discovered solutions almost twice as good as the Darwinian method.