Natural evolution keeps inventing new complex and intricate forms and behaviors. Digital evolution and genetic algorithms fail to create the same kind of complexity, not just because we still lack the computational resources to rival nature, but because (it has been argued) we have not understood in principle how to create open-ended evolving systems. Much effort has been made to define such open-endedness so as to create forms of increasing complexity indefinitely. Here, however, a simple evolving computational system that satisfies all such requirements is presented. Doing so reveals a shortcoming in the definitions for open-ended evolution. The goal to create models that rival biological complexity remains. This work suggests that our current definitions allow for even simple models to pass as open-ended, and that our definitions of complexity and diversity are more important for the quest of open-ended evolution than the fact that something runs indefinitely.

中文翻译：

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为了开放而开放

自然进化不断发明新的复杂的形式和行为。数字进化和遗传算法未能创造出同样的复杂性，不仅因为我们仍然缺乏与自然竞争的计算资源，还因为（有人争论）我们原则上还没有理解如何创建开放式进化系统。已经付出了很多努力来定义这种开放性，从而无限期地创造出越来越复杂的形式。然而，这里提出了一个满足所有这些要求的简单演进计算系统。这样做揭示了开放式进化定义中的一个缺点。创建与生物复杂性相媲美的模型的目标仍然存在。这项工作表明，我们当前的定义甚至允许简单的模型作为开放式模型通过，