AgentNet

Pytorch implementation of AgentNet, which is designed for reveal hidden interactions and predict future dynamics of the unknown complex system. Paper : https://arxiv.org/abs/2001.02539

model

• AgentNet architectures for each model, Cellular Automata (CA), Vicsek model (VC), Active Ornstein-Uhlenbeck Particle(AOUP), and Chimney Swift flock (CS).

src

• Main source code includes utilities and loss functions.

train

• Training code for each model.
• Currently in multi-GPU settings (with DistributedDataParallel).

data_generation

• Generates training/test dataset for the model systems.
• Produced dataset needs to be placed in './data/{CA, Vicsek, AOUP}', respectively for further training.

data_generation_cs

• This code needs pre-processed system data from the original chimney swift trajectory data (Evangelista, D. J. et al., Three-dimensional trajectories and network analyses of group behaviour within chimney swift flocks during approaches to the roost, 2017, https://royalsocietypublishing.org/doi/full/10.1098/rspb.2016.2602).
• The pre-procssed data is uploaded at (https://zenodo.org/record/5084183#.YOft42gzaUl), and needs to be placed in './data/Flock/system'
• The produced dataset needs to be placed in './data/Flock/dataset'for further training.

Figures

• Supplementary figures for manuscript.
• Additional attention analysis for different variables (for AOUP and CS).