Visualizing Evolutionary Dynamics of Self-Replicators Using Graph-Based Genealogy
We present a general method for evaluating and visualizing evolutionary dynamics of self-replicators using a graph-based representation for genealogy. Through a transformation from the space of species and mutations to the space of nodes and links, evolutionary dynamics are understood as a flow in graph space. Mapping functions are introduced to translate graph nodes to points in an n-dimensional visualization space for interpretation and analysis. Using this scheme, we evaluate the effect of a dynamic environment on a population of self-reproducing loops. Resulting images visually reveal the critical role played by genealogical graph space partitioning in the evolutionary process.
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