Unified Simulation of Isomorphisms Between Ant Colony Intelligence and Machine Learning

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Documentation for package ‘AntsNet’ version 1.0.0

• DESCRIPTION file
• Package README

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AntsNet-package	AntsNet: Unified Simulation of Ant Colony / Machine Learning Isomorphisms
acar	Ant Colony Adaptive Recruitment (ACAR)
adaboost	AdaBoost with Decision Stumps
AntsNet	AntsNet: Unified Simulation of Ant Colony / Machine Learning Isomorphisms
calculate_margins	Calculate Boosting Margins
calculate_quorum_margin	Calculate Quorum Margin
colony_variance_experiment	Experiment 2: Ant Colony Variance Decomposition
convergence_experiment_boost	Convergence Rate Experiment
create_isomorphism_schematic	Figure 1: Isomorphism Schematic
find_best_stump	Find the Best Decision Stump
gacl	Generational Ant Colony Learning (GACL)
generate_all_figures	Generate All Manuscript Figures
generate_classification_data	Generate Synthetic Classification Data
generate_regression_data	Generate Synthetic Regression Data
generate_synthetic_data	Generate Synthetic Classification Data
isomorphism_test	Experiment 3: Direct Isomorphism Test
launch_app	Launch an Interactive Shiny App
noise_experiment_boost	Noise Robustness Experiment
optimal_decorrelation_experiment	Experiment 4: Optimal Decorrelation
plot_colony_accuracy	Supplementary: Colony Accuracy vs Size
plot_convergence_boost	Plot Figure 4: Convergence Rates
plot_convergence_complexity	Plot Convergence Across Complexity (Figure 6)
plot_correlation_decay	Figure 3: Correlation Decay Comparison
plot_gradient_dynamics	Plot Gradient Dynamics (Figure 7)
plot_isomorphism	Plot the Gradient Descent Isomorphism (Figure 1)
plot_learning_curves	Plot Learning Curves with Replicates (Figure 2)
plot_learning_rate_sensitivity	Plot Learning Rate Sensitivity (Figure 4)
plot_margin_quorum	Plot Figure 3: Margin vs Quorum
plot_noise_robustness_boost	Plot Figure 5: Noise Robustness
plot_noise_robustness_nn	Plot Noise Robustness (Figure 5)
plot_optimal_decorrelation	Figure 4: Optimal Decorrelation
plot_pheromone_weight	Plot Pheromone vs Weight Evolution (Figure 3)
plot_plasticity	Plot Plasticity and Adaptation (Figure 8)
plot_sensitivity_heatmap	Figure 5: Sensitivity Heat-map
plot_variance_decomposition	Figure 2: Variance Decomposition
plot_weak_learnability	Plot Figure 1: Weak Learnability Theorem
plot_weight_pheromone	Plot Figure 2: Weight vs Pheromone Evolution
predict_adaboost	Predict with an AdaBoost Ensemble
predict_stump	Predict with a Decision Stump
sensitivity_analysis	Experiment 5: Sensitivity Analysis
simple_neural_network	Simple Neural Network with Stochastic Gradient Descent
simulate_ant_colony	Simulate an Ant Colony Decision Process
sim_boost_recruitment	Boosting and Adaptive Recruitment Simulation
sim_colony_convergence	Colony Convergence Simulation
sim_decorrelation	Decorrelation Parameter Sweep
sim_gradient_colony	Gradient Descent and Generational Colony Learning
sim_margin_analysis	Margin Analysis
sim_plasticity	Plasticity and Environmental Adaptation
sim_variance_decomp	Variance Decomposition Simulation
test_isomorphism	Test Isomorphism Between Two Learning Curves
track_weights	Track AdaBoost Weight Evolution
variance_decomposition_experiment	Experiment 1: Random Forest Variance Decomposition
weak_learnability_experiment	Weak Learnability Experiment
within_colony_correlation	Compute Within-Colony Ant Correlation