Department of Computer Science and Engineering, Michigan State University, Easting Lansing, MI, USA.
Artif Life. 2011 Winter;17(1):1-20. doi: 10.1162/artl_a_00014. Epub 2010 Nov 18.
We present a study in the evolution of temporal behavior, specifically synchronization and desynchronization, through digital evolution and group selection. In digital evolution, a population of self-replicating computer programs exists in a user-defined computational environment and is subject to instruction-level mutations and natural selection. Group selection links the survival of the individual to the survival of its group, thus encouraging cooperation. Previous approaches to engineering synchronization and desynchronization algorithms have taken inspiration from nature: In the well-known firefly model, the only form of communication between agents is in the form of flash messages among neighbors. Here we demonstrate that populations of digital organisms, provided with a similar mechanism and minimal information about their environment, are capable of evolving algorithms for synchronization and desynchronization, and that the evolved behaviors are robust to message loss. We further describe how the evolved behavior for synchronization mimics that of the well-known Ermentrout model for firefly synchronization in biology. In addition to discovering self-organizing behaviors for distributed computing systems, this result indicates that digital evolution may be used to further our understanding of synchronization in biology.
我们通过数字进化和群体选择来研究时间行为的演化，特别是同步和去同步。在数字进化中，一群自我复制的计算机程序存在于用户定义的计算环境中，并受到指令级别的突变和自然选择的影响。群体选择将个体的生存与群体的生存联系起来，从而鼓励合作。以前的工程同步和去同步算法的方法都受到了自然的启发：在著名的萤火虫模型中，代理之间唯一的通信形式是邻居之间的闪光消息。在这里，我们证明了提供类似机制和关于环境的最小信息的数字生物群体能够进化出用于同步和去同步的算法，并且进化出的行为对消息丢失具有鲁棒性。我们进一步描述了同步的进化行为如何模拟生物学中著名的萤火虫同步的 Ermentrout 模型。除了发现分布式计算系统的自组织行为外，这一结果表明，数字进化可以用来进一步理解生物学中的同步。
