Genetic Variation and the Evolution of Consensus in Digital Organisms
Genetic Variation and the Evolution of Consensus in Digital Organisms
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数字生物体的遗传变异和共识的演变
DOI：
10.1109/tevc.2012.2201725
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发表时间：
2013
影响因子：
14.3
通讯作者：
P. McKinley
中科院分区：
文献类型：
--
作者：
David B. Knoester;Heather Goldsby;P. McKinley
在本文中，我们描述了一个研究的共识，合作的行为，其中成员在同质和异质的群体，必须同意在他们的环境中感测到的信息的演变。我们使用数字进化进行了这项研究，这是一种进化计算的形式，其中计算机程序（数字生物体）存在于用户定义的计算环境中，并受到进化水平突变和自然选择的影响。我们将这些数字生物分成不同的群体，这些群体的适应性取决于它们达成共识的能力。然后，我们测试了不同程度和类型的遗传变异存在于人口中，基于生物启发模型的基因流，包括突变，性重组，迁移和水平基因转移。我们的实验处理检查了这些过程对遗传变异和群体达成共识的能力的影响。这些实验的结果表明，虽然群体内的遗传异质性增加了共识任务的难度，但数量惊人的群体能够克服这些障碍并进化出这种合作行为。
In this paper, we describe a study of the evolution of consensus, a cooperative behavior in which members in both homogeneous and heterogeneous groups, must agree on information sensed in their environment. We conducted the study using digital evolution, a form of evolutionary computation where a population of computer programs (digital organisms) exists in a user-defined computational environment and is subject to instruction-level mutations and natural selection. We placed these digital organisms into groups whose fitness relied upon their ability to perform consensus. We then tested different degrees and types of genetic variation present in the population, based on biologically inspired models of gene flow, including mutation, sexual recombination, migration, and horizontal gene transfer. Our experimental treatments examined the effect of these processes on genetic variation and groups' ability to reach consensus. The results of these experiments demonstrate that while genetic heterogeneity within groups increases the difficulty of the consensus task, a surprising number of groups were able to overcome these obstacles and evolve this cooperative behavior.
DOI：
10.1073/pnas.0602530103
发表时间：
2006-07-18
影响因子：
11.1
作者：
Traulsen, Arne;Nowak, Martin A.
通讯作者：
Nowak, Martin A.