arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2009.09515nlin.CGcs.FL
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复杂元胞自动机的随机展开方法

Random Expansion Method for the Generation of Complex Cellular Automata

Juan Carlos Seck-Tuoh-Mora, Norberto Hernandez-Romero, Joselito Medina-Marin, Genaro J. Martinez, Irving Barragan-Vite

摘要:

元胞自动机中复杂行为的出现是近年来广泛发展的一个领域,其目的是生成和分析产生空间移动模式的自动机或在周期性背景中相互作用的滑翔机。通常,这种类型的自动机是通过穷举搜索或精心构建进化规则而发现的。在这项研究中,具有复杂行为的元胞自动机的规格说明,通过使用随机生成的样本。特别是,它提出了一个元胞自动机的$n$状态应指定随机,然后扩展到另一个自动机与更多的国家,使原来的自动机作为一个周期性的背景下,额外的国家用于定义滑翔机。此外,本研究还对这种方法进行了解释。此外,利用平均场近似和局部熵测度研究了复杂元胞自动机的随机定义方法。该规范用遗传算法进行了改进,以获得具有更高复杂度的样本。使用这种方法,可以生成具有数百个状态的复杂自动机,这表明随机定义的具有多个状态的局部交互可以构建复杂性。

英文摘要:

The emergence of complex behaviors in cellular automata is an area that has been widely developed in recent years with the intention to generate and analyze automata that produce space-moving patterns or gliders that interact in a periodic background. Frequently, this type of automata has been found through either an exhaustive search or a meticulous construction of the evolution rule. In this study, the specification of cellular automata with complex behaviors was obtained by utilizing randomly generated specimens. In particular, it proposed that a cellular automaton of $n$ states should be specified at random and then extended to another automaton with a higher number of states so that the original automaton operates as a periodic background where the additional states serve to define the gliders. Moreover, this study presented an explanation of this method. Furthermore, the random way of defining complex cellular automata was studied by using mean-field approximations for various states and local entropy measures. This specification was refined with a genetic algorithm to obtain specimens with a higher degree of complexity. With this methodology, it was possible to generate complex automata with hundreds of states, demonstrating that randomly defined local interactions with multiple states can construct complexity.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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