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An elegant PyTorch deep reinforcement learning library.
Decentralized reinforcement learning for city-scale traffic light control
Source Code for paper "Joint Computing, Pushing and Caching Optimization for Mobile Edge Computing Networks via Soft Actor-Critic Learning"
The source code for the paper titled Combinatorial Client-Master Multiagent Deep Reinforcement Learning for Task Offloading in Mobile Edge Computing
Communication-Efficient Federated Learning through Adaptive Weight Clustering and Server-Side Distillation
Source code for paper 'An Improved Federated Learning Algorithm for Privacy-Preserving in Cybertwin-Driven 6G System'
Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
Build your neural network easy and fast, 莫烦Python中文教学
This is a library that provides dual dexterous hand manipulation tasks through Isaac Gym
Implementation of SNAIL(A Simple Neural Attentive Meta-Learner) with Gluon
Implementation of VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning - Zintgraf et al. (ICLR 2020)
Reinforcement Learning with Model-Agnostic Meta-Learning in Pytorch
Proximal Policy Optimization with Model-Agnostic Meta-Learning for Battery Energy Storage System Management in a Multi-Microgrid
Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.
A collection of Meta-Reinforcement Learning algorithms in PyTorch
Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.