Selecting continuous life-like cellular automata for halting unpredictability: evolving for abiogenesis

Selecting continuous life-like cellular automata for halting unpredictability: evolving for abiogenesis
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选择连续的栩栩如生的细胞自动机来阻止不可预测性:自然发生的进化

DOI:
10.1145/3520304.3529037
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发表时间:
2022
期刊:
Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '22
影响因子:
--
通讯作者:
Bongard, Josh
Bongard, Josh
中科院分区:
--
文献类型:
--
作者:
Davis, Q. Tyrell;Bongard, Josh

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大量的工作已经应用到工程CA与期望的紧急性质,如支持滑翔机。最近在连续CA方面的工作已经产生了各种各样引人注目的生物记忆模式,并且将CA研究扩展到连续值域、多通道和更高维度使其研究复杂化。在这项工作中,我们设计了一种分两步发展CA和CA模式的策略,基于这样一个简单的想法:如果CA支持无限增长的模式和完全消失的模式,并且难以提前预测差异,那么CA可能是复杂的和具有计算能力的。我们策略的第二部分通过选择移动性和平均细胞值的保存来进化模式。我们通过重新发现17个Lenia CA中的17个滑翔机来验证我们的模式进化方法,并报告了4个新的进化CA和1个随机进化CA,这些CA支持新的进化滑翔机模式。这里报告的CA与前面描述的Lenia CA共享邻域内核,但表现出比Lenia CA更广泛的典型动态。持续演进CA的代码在MIT许可下提供。
Substantial efforts have been applied to engineer CA with desired emergent properties, such as supporting gliders. Recent work in continuous CA has generated a wide variety of compelling bioreminiscent patterns, and the expansion of CA research into continuously-valued domains, multiple channels, and higher dimensions complicates their study. In this work we devise a strategy for evolving CA and CA patterns in two steps, based on the simple idea that CA are likely to be complex and computationally capable if they support patterns that grow indefinitely as well as patterns that vanish completely, and are difficult to predict the difference in advance. The second part of our strategy evolves patterns by selecting for mobility and conservation of mean cell value. We validate our pattern evolution method by re-discovering gliders in 17 of 17 Lenia CA, and also report 4 new evolved CA and 1 randomly evolved CA that support novel evolved glider patterns. The CA reported here share neighborhood kernels with previously described Lenia CA, but exhibit a wider range of typical dynamics than their Lenia counterparts. Code for evolving continuous CA is made available under an MIT License1.
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