Power law dynamics in genealogical graphs
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Several populational networks present complex topologies when implemented in evolutionary algorithms. A common feature of these topologies is the emergence of a power law. In genealogical networks, the power law can be observed by measuring the impact of individuals in the population, which can be calculated through the Event Takeover Value (ETV) algorithm. In this paper, we show evidence that the different power-law deviations, resulting from the ETV distributions of genealogical graphs, are static images of a dynamic evolution that can be well described by q-exponential distribution.
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