landoufulxf's repositories
DRL-robot-navigation
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 goal point in a simulated environment while avoiding obstacles.
trip-card
xck
panda-gym
OpenaAI Gym Franka Emika Panda robot environment based on PyBullet.
robogym
Robotics Gym Environments
BCQ
Author's PyTorch implementation of BCQ for continuous and discrete actions
DL_RL_Zoo
Lightweight, stable, efficient PyTorch implement of reinforcement learning. I want to call this PyTorch implement as "3-Python-file-RL".
curious
Implementation of CURIOUS: Intrinsically Motivated Modular Multi-Goal Reinforcement Learning
deeprl_signal_control
multi-agent deep reinforcement learning for large-scale traffic signal control.
rl-tutorial-jnrr19
Stable-Baselines tutorial for Journées Nationales de la Recherche en Robotique 2019
Multi-Agent-Reinforcement-Learning-Environment
Hello, I pushed some python environments for Multi Agent Reinforcement Learning.
DRL4Recsys
Courses on Deep Reinforcement Learning (DRL) and DRL papers for recommender systems
Deep-Learning-with-PyTorch-Tutorials
深度学习与PyTorch入门实战视频教程 配套源代码和PPT
Adaptive-Traffic-Signal-Control-Using-Reinforcement-Learning
This is an application exploiting principles of Deep Reinforcement Learning. The Deep Neural Network is trained to approximate the Bellman Equation (Q-Learning).
DeepRL-1
Deep Reinforcement Learning Lab, a platform designed to make DRL technology and fun for everyone
pg-is-all-you-need
Policy Gradient is all you need! A step-by-step tutorial for well-known PG methods.
rainbow-is-all-you-need
Rainbow is all you need! A step-by-step tutorial from DQN to Rainbow
colight
CoLight: Learning Network-level Cooperation for Traffic Signal Control
QuadrotorFly
This is a dynamic simulation for quadrotor UAV
Deep-QLearning-Agent-for-Traffic-Signal-Control
A framework where a deep Q-Learning Reinforcement Learning agent tries to choose the correct traffic light phase at an intersection to maximize the traffic efficiency.
tensorwatch
Debugging, monitoring and visualization for Python Machine Learning and Data Science
DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
mep
Maximum Entropy-Regularized Multi-Goal Reinforcement Learning (ICML 2019)
gym-platform
OpenAI Gym environment for Platform
MP-DQN
Source code for the dissertation: "Multi-Pass Deep Q-Networks for Reinforcement Learning with Parameterised Action Spaces"
practicalAI
📚 A practical approach to learning and using machine learning.
Recommenders
Best Practices on Recommendation Systems
gymfc
An OpenAI environment for developing neuro-flight controllers using reinforcement learning