Implementation and application of graph theory, social network mining, reinforcement learning, and inverse reinforcement learning.
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Updated
Sep 27, 2021 - Jupyter Notebook
Implementation and application of graph theory, social network mining, reinforcement learning, and inverse reinforcement learning.
Complex networks such as ER, BA networks and many more :)
This project is a visualization of the network science models. Uses CytoScape.js to visualize the models.
Models of Bak-Tang-Wiesenfeld, Manna, Feders and stochastic Feders sand piles on cellular automaton and random graphs in Python 3
Реализация программы-калькулятора для вычисления характеристик случайных графов // Implementation of program for calculating characteristics of random graphs
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