graph_learning_social_interactions_2021

This is the code that corresponds to the simulations performed in two papers

V. Shumovskaia, K. Ntemos, S. Vlaski and A. H. Sayed, "Online Graph Learning from Social Interactions," 2021 55th Asilomar Conference on Signals, Systems, and Computers, 2021, pp. 1263-1267. 10.1109/IEEECONF53345.2021.9723403

V. Shumovskaia, K. Ntemos, S. Vlaski and A. H. Sayed, "Explainability and Graph Learning from Social Interactions," IEEE Transactions on Signal and Information Processing over Networks, vol. 8, pp. 946–959, 2022. DOI:10.1109/TSIPN.2022.3223805

Usage

To run experiments, we refer to runs_final.txt, e.g.:

python main.py --likelihood_regime 0 --times 20000 --adjacency_regime 3 --agents 30 --er_prob 0.2 --seed 25 --lr 0.1 --step_size 0.1 --likelihood_var 0.5 --multistate --states 10

To understand arguments for the parser we refer to parser.py or run python main.py --help.

Author: Valentina Shumovskaia