In Silico Population Model

The work develops an agent-based in silico model in which virtual individuals carry genomes encoding age-specific survival and reproduction probabilities. The study used an adaptive agent-based model with evolvable age-specific survival and reproduction rates. Individuals age at velocity 1 in the model. Birth occurs at an age- and trait-dependent rate, with mutant newborns receiving trait x+h and age 0. The microscopic model is a continuous-time Markov process on finite point measures over trait-age space. Death includes natural death and competitive effects from other individuals. Agents advanced through discrete life stages from 0 to 101 and died automatically at stage 101. The model imposed a fixed resource constraint that triggers famine when the population exceeds 1000. The model uses overlapping generations and discrete time intervals called stages. Each genome contains survival modules, reproduction modules, and a neutral region with no phenotypic effect. Mating required both spatial proximity and nuclear genetic compatibility. Fitness followed a Gaussian function in which smaller sigma_w represented stronger selection. Species emerged from gene-flow network components rath…