Repo for the Deep Reinforcement Learning Nanodegree program
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Updated
Jul 20, 2022 - Jupyter Notebook
Repo for the Deep Reinforcement Learning Nanodegree program
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.
This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch
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
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
Tensorflow 2 Reinforcement Learning Cookbook, published by Packt
Our VMAgent is a platform for exploiting Reinforcement Learning (RL) on Virtual Machine (VM) scheduling tasks.
Reinforcement learning algorithms
Code for "Constrained Variational Policy Optimization for Safe Reinforcement Learning" (ICML 2022)
Multi-Objective Reinforcement Learning algorithms implementations.
Implementation notebooks and scripts of Deep Reinforcement learning Algorithms in PyTorch and TensorFlow.
RL-Toolkit: A Research Framework for Robotics
This repository has RL algorithms implemented using python
Toy case for learning through Reinforcement Learning algorithms how to establish TCP connections.
Reinforcement Learning framework for learning IoT interactions.
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