[Paper Review] An Artificial Life Simulation Library Based on Genetic Algorithm, 3-Character Genetic Code and Biological Hierarchy

Maurice HT Ling|Feb 19, 2023

Evolution and Genetic Dynamics32 references8 citations

TL;DR

The paper presents DOSE, a Python library for artificial life simulation using a genetic algorithm with a 3-character, operand-free genetic code and a 3D ecological cellular world to study mutations and evolution.

ABSTRACT

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.

Motivation & Objective

• Motivate the use of genetic algorithms to model real-life evolutionary processes in artificial life systems.
• Design a Python library (DOSE) that encodes digital organisms with a 3-character genetic code inspired by codons in DNA.
• Incorporate a 3D ecological world structure to simulate interactions across levels from genes to populations.
• Investigate how mutation rates affect changes in genetic sequences within the simulated ecosystem.

Proposed method

• Introduce DOSE, a Python-based library for artificial life simulation built on genetic algorithms.
• Adopt a 3-character, operand-free genetic code to mimic 3-nucleotide codon structure.
• Model a 3D world composed of ecological cells to create a spatially structured ecosystem.
• Trace the evolutionary process from genetic sequences to population dynamics within biological hierarchy.
• Conduct experiments to examine how varying mutation rates influence genetic sequence changes.

Experimental results

Research questions

• RQ1 How does a 3-character, operand-free genetic code influence the evolution of digital organisms in DOSE?
• RQ2 What is the impact of different mutation rates on genetic sequence dynamics within the 3D ecological world?
• RQ3 How does the biological hierarchy—from genetic sequence to population—shape emergent evolutionary outcomes in the simulation?

Key findings

• DOSE demonstrates how mutation rate variations affect genetic sequence changes in a digital life setting.
• The 3-character genetic code allows a codon-like encoding without operands, influencing evolutionary dynamics in the simulated ecosystem.
• The 3D ecological cell framework supports exploration of spatial and hierarchical interactions in artificial life.
• The study provides a platform to study evolutionary processes by linking genotype to population-level outcomes.