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AGen

Adaptable generative prediction using recursive least square algorithm

Install / Use

/learn @intelligent-control-lab/AGen
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

Details for running AGen

Setup Environment

  • install dependancy and data preprocessing see full_preprocessing_demon.md please modify dataset file name in validate_utils.py & adaption.py

  • Install AGen clone files in this reporsitory directly to YOURPATH/ngsim_env/scripts/imitation

  • Pretrained model and hyperparameters copy .npz files in ./pretrained/ to YOURPATH/ngsim_env/data/experiments/multiagent_curr/imitate/log/

Run Code

# Train and run a single agent adaptive algorithm
python adaption.py --n_proc 1 --exp_dir ../../data/experiments/multiagent_curr/ --params_filename itr_200.npz --use_multiagent True --n_envs 22 --adapt_steps 1(or2) 
# Train and run a single/multi adaptive algorithm
python adaption.py --n_proc 1 --exp_dir ../../data/experiments/multiagent_curr/ --params_filename itr_200.npz --use_multiagent False --n_envs 1 --adapt_steps 1(or2)

Supporting files

  • theta.npy extracted top layer for pretrained RNN, use as initialization

  • check_convergence.py check whether pretrained GAN is valid

Data Generation

output .npz file will be in YOURPATH/ngsim_env/data/experiments/multiagent_curr/imitate/

Data Analysis

a reference analysis example see data_analysis.ipynb

View on GitHub
GitHub Stars15
CategoryDevelopment
Updated1y ago
Forks3

Languages

Jupyter Notebook

Security Score

80/100

Audited on Aug 13, 2024

No findings