论文标题
家谱图中的电力法动力学
Power law dynamics in genealogical graphs
论文作者
论文摘要
在进化算法中实现时，几个人口网络会呈现复杂的拓扑结构。这些拓扑的一个共同特征是权力法的出现。在家谱网络中也可以观察到具有不同缩放因素的功率法行为，但我们仍然无法令人满意地描述其动态或随着时间的流逝与人口进化的关系。在本文中，我们使用一种算法来衡量个体在几个数值人群中的影响，并通过无Xtentistion统计研究其进化动力学。这样的证据表明，随着时间的流逝，观察到的权力定律的出现具有动态行为。可以使用Q-指数分布的家族来描述这种动态发展，该分布的参数是时间依赖性并遵循特定模式的。我们还显示了证据表明，精英主义会显着影响观察到的功率定律缩放因素。这些结果表明，在家谱网络中观察到的不同功率定律形状和偏差是时间依赖性动态发展的静态图像，可以使用Q-指数分布来令人满意地描述。
Several populational networks present complex topologies when implemented in evolutionary algorithms. A common feature of these topologies is the emergence of a power law. Power law behavior with different scaling factors can also be observed in genealogical networks, but we still can not satisfactorily describe its dynamics or its relation to population evolution over time. In this paper, we use an algorithm to measure the impact of individuals in several numerical populations and study its dynamics of evolution through nonextensive statistics. Like this, we show evidence that the observed emergence of power law has a dynamic behavior over time. This dynamic development can be described using a family of q-exponential distributions whose parameters are time-dependent and follow a specific pattern. We also show evidence that elitism significantly influences the power law scaling factors observed. These results imply that the different power law shapes and deviations observed in genealogical networks are static images of a time-dependent dynamic development that can be satisfactorily described using q-exponential distributions.
