TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.

A toolkit for reproducible reinforcement learning research.

Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.

Reinforcement Learning environments for Traffic Signal Control with SUMO. Compatible with Gymnasium, PettingZoo, and popular RL libraries.

Implementing Reinforcement Learning, namely Q-learning and Sarsa algorithms, for global path planning of mobile robot in unknown environment with obstacles. Comparison analysis of Q-learning and Sarsa

This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch

Multi-Objective Reinforcement Learning algorithms implementations.

EasyRL: An easy-to-use and comprehensive reinforcement learning package.

Pytorch Implementation of Reinforcement Learning Algorithms ( Soft Actor Critic(SAC)/ DDPG / TD3 /DQN / A2C/ PPO / TRPO)

self-studying the Sutton & Barto the hard way

Our VMAgent is a platform for exploiting Reinforcement Learning (RL) on Virtual Machine (VM) scheduling tasks.

Code for "Constrained Variational Policy Optimization for Safe Reinforcement Learning" (ICML 2022)

Reinforcement learning algorithms

RL-Toolkit: A Research Framework for Robotics

Deep Reinforcement Learning - Implementations and Theory: A path to mastery

Toy case for learning through Reinforcement Learning algorithms how to establish TCP connections.

Reinforcement Learning framework for learning IoT interactions.

Safe Reinforce Learning -> Constraint algorithms to train agents in Safety Gym, paper notes on research papers regarding RL with constraints + optimizer + neural networks, PyTorch implementation on policy gradient algorithms

Custom Reinforcement Learning Agents

Reinforcement learning applied in the game of poker (holdem texas version).