Package: AntsNet 1.0.0

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>).

Authors:Yuval Levental [aut, cre], Gregory Babbitt [aut], Ernest Fokoué [aut]

AntsNet_1.0.0.tar.gz
AntsNet_1.0.0.zip(r-4.7)AntsNet_1.0.0.zip(r-4.6)AntsNet_1.0.0.zip(r-4.5)
AntsNet_1.0.0.tgz(r-4.6-any)AntsNet_1.0.0.tgz(r-4.5-any)
AntsNet_1.0.0.tar.gz(r-4.7-any)AntsNet_1.0.0.tar.gz(r-4.6-any)
AntsNet_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
AntsNet/json (API)

# Install 'AntsNet' in R:
install.packages('AntsNet', repos = c('https://ylevental.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ylevental/isomorphismsim_full/issues

On CRAN:

Conda:

3.18 score 3 scripts 548 downloads 52 exports 80 dependencies

Last updated from:451a19d9cb. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK154
source / vignettesOK184
linux-release-x86_64OK166
macos-release-arm64OK236
macos-oldrel-arm64OK144
windows-develOK99
windows-releaseOK98
windows-oldrelOK100
wasm-releaseOK136

Exports:acaradaboostcalculate_marginscalculate_quorum_margincolony_variance_experimentconvergence_experiment_boostcreate_isomorphism_schematicfind_best_stumpgaclgenerate_all_figuresgenerate_classification_datagenerate_regression_datagenerate_synthetic_dataisomorphism_testlaunch_appnoise_experiment_boostoptimal_decorrelation_experimentplot_colony_accuracyplot_convergence_boostplot_convergence_complexityplot_correlation_decayplot_gradient_dynamicsplot_isomorphismplot_learning_curvesplot_learning_rate_sensitivityplot_margin_quorumplot_noise_robustness_boostplot_noise_robustness_nnplot_optimal_decorrelationplot_pheromone_weightplot_plasticityplot_sensitivity_heatmapplot_variance_decompositionplot_weak_learnabilityplot_weight_pheromonepredict_adaboostpredict_stumpsensitivity_analysissim_boost_recruitmentsim_colony_convergencesim_decorrelationsim_gradient_colonysim_margin_analysissim_plasticitysim_variance_decompsimple_neural_networksimulate_ant_colonytest_isomorphismtrack_weightsvariance_decomposition_experimentweak_learnability_experimentwithin_colony_correlation

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecorrplotcowplotcpp11DerivdoBydplyrfarverforecastFormulafracdiffgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtableisobandlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrnlmenloptrnnetnumDerivpatchworkpbkrtestpillarpkgconfigpolynompurrrquantregR6rangerrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangrstatixS7scalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8vctrsviridisviridisLitewithrzoo

Readme and manuals

Help Manual

Help pageTopics
AntsNet: Unified Simulation of Ant Colony / Machine Learning IsomorphismsAntsNet-package AntsNet
Ant Colony Adaptive Recruitment (ACAR)acar
AdaBoost with Decision Stumpsadaboost
Calculate Boosting Marginscalculate_margins
Calculate Quorum Margincalculate_quorum_margin
Experiment 2: Ant Colony Variance Decompositioncolony_variance_experiment
Convergence Rate Experimentconvergence_experiment_boost
Figure 1: Isomorphism Schematiccreate_isomorphism_schematic
Find the Best Decision Stumpfind_best_stump
Generational Ant Colony Learning (GACL)gacl
Generate All Manuscript Figuresgenerate_all_figures
Generate Synthetic Classification Datagenerate_classification_data
Generate Synthetic Regression Datagenerate_regression_data
Generate Synthetic Classification Datagenerate_synthetic_data
Experiment 3: Direct Isomorphism Testisomorphism_test
Launch an Interactive Shiny Applaunch_app
Noise Robustness Experimentnoise_experiment_boost
Experiment 4: Optimal Decorrelationoptimal_decorrelation_experiment
Supplementary: Colony Accuracy vs Sizeplot_colony_accuracy
Plot Figure 4: Convergence Ratesplot_convergence_boost
Plot Convergence Across Complexity (Figure 6)plot_convergence_complexity
Figure 3: Correlation Decay Comparisonplot_correlation_decay
Plot Gradient Dynamics (Figure 7)plot_gradient_dynamics
Plot the Gradient Descent Isomorphism (Figure 1)plot_isomorphism
Plot Learning Curves with Replicates (Figure 2)plot_learning_curves
Plot Learning Rate Sensitivity (Figure 4)plot_learning_rate_sensitivity
Plot Figure 3: Margin vs Quorumplot_margin_quorum
Plot Figure 5: Noise Robustnessplot_noise_robustness_boost
Plot Noise Robustness (Figure 5)plot_noise_robustness_nn
Figure 4: Optimal Decorrelationplot_optimal_decorrelation
Plot Pheromone vs Weight Evolution (Figure 3)plot_pheromone_weight
Plot Plasticity and Adaptation (Figure 8)plot_plasticity
Figure 5: Sensitivity Heat-mapplot_sensitivity_heatmap
Figure 2: Variance Decompositionplot_variance_decomposition
Plot Figure 1: Weak Learnability Theoremplot_weak_learnability
Plot Figure 2: Weight vs Pheromone Evolutionplot_weight_pheromone
Predict with an AdaBoost Ensemblepredict_adaboost
Predict with a Decision Stumppredict_stump
Experiment 5: Sensitivity Analysissensitivity_analysis
Boosting and Adaptive Recruitment Simulationsim_boost_recruitment
Colony Convergence Simulationsim_colony_convergence
Decorrelation Parameter Sweepsim_decorrelation
Gradient Descent and Generational Colony Learningsim_gradient_colony
Margin Analysissim_margin_analysis
Plasticity and Environmental Adaptationsim_plasticity
Variance Decomposition Simulationsim_variance_decomp
Simple Neural Network with Stochastic Gradient Descentsimple_neural_network
Simulate an Ant Colony Decision Processsimulate_ant_colony
Test Isomorphism Between Two Learning Curvestest_isomorphism
Track AdaBoost Weight Evolutiontrack_weights
Experiment 1: Random Forest Variance Decompositionvariance_decomposition_experiment
Weak Learnability Experimentweak_learnability_experiment
Compute Within-Colony Ant Correlationwithin_colony_correlation