Isomorphic Functionalities between Ant Colony and Ensemble Learning: Part III -- Gradient Descent, Neural Plasticity, and the Emergence of Deep Intelligence
In Parts I and II of this series, we established isomorphisms between ant colony decision-making and two major families of ensemble learning: random forests (parallel, variance reduction) and boosting (sequential, bias reduction). Here we complete the trilogy by demonstrating that the fundamental learning algorithm underlying deep neural networks -- stochastic gradient descent -- is mathematically isomorphic to the generational learning dynamics of ant colonies. We prove that pheromone evolution across generations follows the same update equations as weight evolution during gradient descent, with evaporation rates corresponding to learning rates, colony fitness corresponding to negative l...
| Authors | Ernest Fokoué, Gregory Babbitt, Yuval Levental |
|---|---|
| Primary category | cs.NE |
| Published | 3 April 2026 |
| Last updated at source | 3 April 2026 |
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