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| | ==案例== | | ==案例== |
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| − | In 2020, [[Google]] stated their AutoML-Zero can successfully rediscover classic algorithms such as the concept of neural networks.<ref>{{cite news |last1=Gent |first1=Edd |title=Artificial intelligence is evolving all by itself |url=https://www.sciencemag.org/news/2020/04/artificial-intelligence-evolving-all-itself |accessdate=16 April 2020 |work=Science {{!}} AAAS |date=13 April 2020 |language=en |archive-url=https://web.archive.org/web/20200416222954/https://www.sciencemag.org/news/2020/04/artificial-intelligence-evolving-all-itself |archive-date=16 April 2020 |url-status=dead }}</ref>
| + | * 2020年，Google宣布他们的AutoML-Zero成功重复发现了一些经典的算法，比如神经网络<ref>{{cite news |last1=Gent |first1=Edd |title=Artificial intelligence is evolving all by itself |url=https://www.sciencemag.org/news/2020/04/artificial-intelligence-evolving-all-itself |accessdate=16 April 2020 |work=Science {{!}} AAAS |date=13 April 2020 |language=en |archive-url=https://web.archive.org/web/20200416222954/https://www.sciencemag.org/news/2020/04/artificial-intelligence-evolving-all-itself |archive-date=16 April 2020 |url-status=dead }}</ref>。 |
| − | | + | * 计算机模拟程序Tierra和Avida尝试性地对宏观进化过程的动力学建模。 |
| − | In 2020, Google stated their AutoML-Zero can successfully rediscover classic algorithms such as the concept of neural networks.
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| − | 2020年，谷歌宣布他们的 autol-zero 可以成功地重新发现经典算法，比如神经网络的概念。
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| − | The computer simulations ''[[Tierra (computer simulation)|Tierra]]'' and ''[[Avida]]'' attempt to model [[macroevolution]]ary dynamics.
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| − | The computer simulations Tierra and Avida attempt to model macroevolutionary dynamics.
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| − | Tierra 和阿维达的计算机模拟试图建立宏观进化动力学模型。
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