Published July 11, 2022 | Version v1

Supplementary data - "Learning Reduced Models for Large-Scale Agent-Based Systems"

Authors/Creators

  • 1. Zuse Institute Berlin

Contributors

  • 1. Zuse Institute Berlin, Germany
  • 2. University of Surrey, United Kingdom

Description

This repository contains supplementary data on my PhD thesis "Learning Reduced Models for Large-Scale Agent-Based Systems". Chapters 1-3, 7 and A do not have supplementary data.

Chapter 4

  • Large_deviation_example.zip contains the trajectory for Figure 4.8.
  • mean_exit_time* contains the raw data to compute the mean exit time and standard deviation for the ABM process (JP) and SDE process (CLE). It contains additionally a precomputed mean and standard deviation as well as the corresponding numbers of agents.
  • transition_matrix* contain the computed box discretizations as MATLAB and Numpy files as used for Figures 4.2-4.4, 4.6 and Tables 4.1 and 4.2.

Chapter 5

  • CVM_2021-07-09-15-53_training_data.npz contains the training data for Figure 5.7 a and b.
  • CVM_2021-09-29-07-13_distribution.npz contains the raw data for Figure 5.7 c.
  • The remaining data for Chapter 5 can be found in the related dataset doi.org/10.5281/zenodo.4522119.

Chapter 6

  • CVM_pareto_estimate contains trajectory data required for Figure 6.6 b to estimate points in the Pareto Front using the civil violence model. 
  • CVM_training_data contains the training data to construct the surrogate model. Each data set consists of CVM_*_cops_train.npz as training set, CVM_*_cops_trajectory.npz as sample trajectory and CVM_*_cops.pkl to compute the training data.
  • CVM_covering_iterations_8.mat Pareto set covering after 8 iterations for the civil violence model. Required for Figure 6.6 a.
  • CVM_pareto_set+front.npz is required for Figure 6.6 b. 
  • CVM_surrogate_model.mat contains the surrogate model for the civil violence model
  • Expl_iterations_* contains Pareto set coverings after 8 and 12 iterations for Example 6.1.4 and Figure 6.1.
  • VM_covering_iterations_12.mat contains the Pareto set covering depicted in Figure 6.4 a.
  • VM_ODE_covering_iterations_12_subset_front.mat contains the Pareto set covering depicted in Figure 6.5 and 6.5 c.
  • VM_ODE_covering_iterations_12_subset.mat contains the Pareto set covering depicted in Figure 6.5 and 6.5 d.
  • VM_ODE_covering_iterations_12.mat contains the Pareto set covering depicted in Figure 6.4 b.
  • VM_surrogate_model.mat contains the surrogate model for the extended voter model.
  • VM_test_points_non_pareto.npz contains Non-Pareto points in Figure 6.5 and 6.5 d.
  • VM_test_points_pareto.npz contains Pareto points in Figure 6.5 and 6.5 c.

Notes

This research has been funded by Germany's Excellence Strategy (MATH+: The Berlin Mathematics Research Center, EXC-2046/1, project ID: 390685689) and through Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) through grant CRC 1114 (Scaling Cascades in Complex Systems, project ID: 235221301).

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Additional details

Related works

Is supplemented by
Dataset: 10.5281/zenodo.4522119 (DOI)