Single file implementations of Deep Multi-agent Reinforcement Learning

LeanRL is a fork of CleanRL, where selected PyTorch scripts optimized for performance using compile and cudagraphs.

🚀 A fast safe reinforcement learning library in PyTorch

Source code for the papers: RL for Mitigating Cascading Failures: Targeted Exploration via Sensitivity Factors (NeurIPS) / Blackout Mitigation via Physics-guided RL (IEEE TPS). Built with TensorFlow.

Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)

RL2Grid is a standardized benchmark for reinforcement learning (RL) agents in realistic power grid environments. Built on top of Grid2Op, it models real-time operations such as topology optimizatio…

A framework to design Reinforcement Learning environments that model Active Network Management (ANM) tasks in electricity distribution networks.

This repository contains an implementation of a UAV-based task offloading model using the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) reinforcement learning algorithm.

The Flatland Framework is a multi-purpose environment to tackle problems around resilient resource allocation under uncertainty. It is designed to be a flexible and method agnostic to solve a wide …

[IEEE TAI] Safe Multi-Agent Reinforcement Learning to Make decisions in Autonomous Driving.

A high-capacity ride-sharing simulator calibrated by real request datasets and road netwoeks

The source code for the blog post The 37 Implementation Details of Proximal Policy Optimization

A Fair and Scalable Time Series Forecasting Benchmark and Toolkit.

PyTorch implementation of Constrained Reinforcement Learning for Soft Actor Critic Algorithm

A clean and robust Pytorch implementation of SAC on discrete action space

Official code repo for the MARL book (www.marl-book.com)

Meta-RL Model-Based Algorithm

🙃 A delightful community-driven (with 2,400+ contributors) framework for managing your zsh configuration. Includes 300+ optional plugins (rails, git, macOS, hub, docker, homebrew, node, php, python…

Explanation to key concepts in ML

[TNNLS-2024, arXiv-2023.2.10] Official repository of "A Survey on Causal Reinforcement Learning"

Official implementation for the NeurIPS 2023 paper: "Reduced Policy Optimization for Continuous Control with Hard Constraints"

Official Repository for "Eureka: Human-Level Reward Design via Coding Large Language Models" (ICLR 2024)

A collection of useful .gitignore templates

Bonus materials, exercises, and example projects for our Python tutorials

Deep Q-Network (DQN) and Fitted Q-Iteration (FQI) tutorial for RL Summer School 2023

Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement Learning

Code implementation for the NeurIPS 2022 paper "Policy Optimization with Advantage Regularization for Long-Term Fairness in Decision Systems".

Transform any arXiv papers into slides using LLMs