Repo for the Deep Reinforcement Learning Nanodegree program
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Updated
Nov 16, 2023 - 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.
Reinforcement Learning environments for Traffic Signal Control with SUMO. Compatible with Gymnasium, PettingZoo, and popular RL libraries.
This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch
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
Multi-Objective Reinforcement Learning algorithms implementations.
Pytorch Implementation of Reinforcement Learning Algorithms ( Soft Actor Critic(SAC)/ DDPG / TD3 /DQN / A2C/ PPO / TRPO)
EasyRL: An easy-to-use and comprehensive reinforcement learning package.
Tensorflow 2 Reinforcement Learning Cookbook, published by Packt
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
Implementation notebooks and scripts of Deep Reinforcement learning Algorithms in PyTorch and TensorFlow.
RL-Toolkit: A Research Framework for Robotics
reinforcement learning DQN method to solve OpenAi Gym "LunarLander-v2" by usnig a Deep Neuralnetwork
This repository has RL algorithms implemented using python
Deep Reinforcement Learning - Implementations and Theory: A path to mastery
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