Ancestry Mapping in Genetic Algorithms: A Didactic Visualization Inspired by Greek Mythology

This work presents a metaphorical implementation of genetic ancestry tests in a Genetic Algorithm (GA), aiming to visually map gene transmission across generations. A predictive categorical model was developed using GA, where individuals were represented by chromosomes composed of real-valued genes. The GA was applied to classify gender based on physical traits such as age, height, weight, and footwear. A novel visualization was implemented in Wolfram Language using color patterns to trace genetic ancestry and mutation history. To enhance didactic appeal, individuals were named after Greek mythological figures — from Titans to Demigods. This approach allowed the ancestry of each individual to be visually tracked, including mutation events and inheritance patterns. Notably, the fittest individual emerged not from the top ancestor, but from a specific combination of genes and beneficial mutations. The proposed visualization offers an intuitive and educational strategy for understanding gene propagation and selection in evolutionary computation.