AntsNet - 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" (Fokoué, Babbitt, and Levental, 2026,
<doi:10.48550/arXiv.2603.20328>,
<doi:10.48550/arXiv.2604.00038>).
