  Genetic algorithm (GA) is inspired by biological evolution of genetic
organisms by optimizing the genotypic combinations encoded within each
individual with the help of evolutionary operators, suggesting that GA may be a
suitable model for studying real-life evolutionary processes. This paper
describes the design of a Python library for artificial life simulation,
Digital Organism Simulation Environment (DOSE), based on GA and biological
hierarchy starting from genetic sequence to population. A 3-character
instruction set that does not take any operand is introduced as genetic code
for digital organism. This mimics the 3-nucleotide codon structure in naturally
occurring DNA. In addition, the context of a 3-dimensional world composing of
ecological cells is introduced to simulate a physical ecosystem. Using DOSE, an
experiment to examine the changes in genetic sequences with respect to mutation
rates is presented.
