Geb was the first artificial life system to be classified as exhibiting open-ended evolutionary dynamics according to Bedau and Packard's evolutionary activity measures and is the only one to have been classified as such according to the enhanced version of that classification scheme. Its evolution is driven by biotic selection, that is (approximately), by natural selection rather than artificial selection. Whether or not Geb can generate an indefinite increase in maximum individual complexity is evaluated here by scaling two parameters: world length (which bounds population size) and the maximum number of neurons per individual. Maximum individual complexity is found to be asymptotically bounded when scaling either parameter alone. However, maximum individual complexity is found to be indefinitely scalable, to the extent evaluated so far (with run times in years and billions of reproductions per run), when scaling both world length and the maximum number of neurons per individual together. Further, maximum individual complexity is shown to scale logarithmically with (the lower of) maximum population size and maximum number of neurons per individual. This raises interesting questions and lines of thought about the feasibility of achieving complex results within open-ended evolutionary systems and how to improve on this order of complexity growth.

中文翻译：

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Geb 中最大个体复杂度是无限可扩展的

根据 Bedau 和 Packard 的进化活动测量，Geb 是第一个被归类为展示开放式进化动力学的人工生命系统，并且是唯一一个根据该分类方案的增强版本被归类为此类的人工生命系统。它的进化是由生物选择驱动的，也就是说（大约）是由自然选择而不是人工选择驱动的。通过缩放两个参数来评估 Geb 是否可以无限增加最大个体复杂性：世界长度（限制种群大小）和每个个体的最大神经元数量。当单独缩放任一参数时，发现最大个体复杂性是渐近有界的。然而，发现最大的个体复杂性是无限可扩展的，到目前为止评估的程度（以年为单位的运行时间和每次运行的数十亿次复制），当同时缩放世界长度和每个个体的最大神经元数量时。此外，最大个体复杂性显示为与最大种群大小和每个个体的最大神经元数量（两者中的较小者）成对数缩放。这提出了有趣的问题和思路，即在开放式进化系统中实现复杂结果的可行性以及如何改进这种复杂性增长的顺序。最大个体复杂性显示为与最大种群大小和每个个体的最大神经元数量（两者中的较小者）成对数缩放。这提出了有趣的问题和思路，即在开放式进化系统中实现复杂结果的可行性以及如何改进这种复杂性增长的顺序。最大个体复杂性显示为与最大种群大小和每个个体的最大神经元数量（两者中的较小者）成对数缩放。这提出了一些有趣的问题和思路，即在开放式进化系统中实现复杂结果的可行性以及如何改进这种复杂性增长的顺序。