Unified Simulation of Isomorphisms Between Ant Colony Intelligence and Machine Learning // Implements the full suite of simulation, visualization, and analysis tools for exploring the mathematical isomorphisms between ant colony decision- making and three major paradigms of machine learning: random forests (Part I: variance reduction through decorrelation), boosting (Part II: bias reduction through adaptive recruitment), and neural networks (Part III: gradient-based generational learning). Accompanies the trilogy "Isomorphic Functionalities between Ant Colony and Ensemble Learning" (Fokou, Babbitt, and Levental, 2026, doi:10.48550/arXiv.2603.20328, doi:10.48550/arXiv.2604.00038).