Python Implementation of Reinforcement Learning: An Introduction

PyTorch implementations of deep reinforcement learning algorithms and environments

Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random g…

Incorporating Transformer and LSTM to Kalman Filter with EM algorithm

An Abstract Cyber Security Simulation and Markov Game for OpenAI Gym

Final project for "Control systems for robotics" - simulation of obstacle avoidance on an autonomous car using MPC

Expectation-Maximization (EM) algorithm in Matlab

A library for mean-field games.

Robot obstacle avoidance with reinforcement learning

Gradient descent methods for Bayesian variational inference with mean field approximation.

战五渣学习日志记录

Implement 2D Ising model using mean field theory, Onsager's formula and Monte Carlo simulation. Course project of Thermodynamics and Statistical Mechanics.

Bayesian Multi-type Mean Field Multi-agent Imitation Learning

Mean field variational Gaussian process algorithm. This repository contains a python3 implementation of the variational mean field algorithm as described in the paper: Physical Review E. vol. 91, 2…

This is the coded used in my master's thesis to simulate an iterative stochastic model that is used to approximate network dynamics as a stochastic mean field.

A framework for solving high-dimensional mean field games (MFG) with normalizing flows (NF) and regularizing NFs with MFG transport costs.