Reinforcement Learning Tutorial Github

10 GitHub Repositories to Master Reinforcement Learning Learn reinforcement learning using free resources, including books, frameworks, courses, tutorials, example code, and projects. By Abid Ali Awan , KDnuggets Assistant Editor on December 2, 2024 in Machine Learning

These best 10 reinforcement learning repositories on GitHub represent the most respected, well-documented, and widely used tools in the RL ecosystem. Whether you're building production-grade agents, conducting cutting-edge research, or just getting started, these repositories will accelerate your journey in the field of AI and machine learning.

Tutorial 1 Q-learning Tutorial 2 SARSA Tutorial 3 Exploring OpenAI gym Tutorial 4 Q-learning in OpenAI gym Tutorial 5 Deep Q-learning DQN Tutorial 6 Deep Convolutional Q-learning Tutorial 7 Reinforcement Learning with ROS and Gazebo Tutorial 8 Reinforcement Learning in DOOM unfinished Tutorial 9 Deep Deterministic Policy

Our environment is deterministic, so all equations presented here are also formulated deterministically for the sake of simplicity. In the reinforcement learning literature, they would also contain expectations over stochastic transitions in the environment.

Reinforcement Learning Algorithms Tutorial Python This repository shows you theoretical fundamentals for typical reinforcement learning methods model-free algorithms with intuitive but mathematical explanations and several lines of Python code.

This is a tutorial book on reinforcement learning, with explanation of theory and Python implementation. Theory Starting from a uniform mathematical framework, this book derives the theory and algorithms of reinforcement learning, including the algorithms in large model era such as PPO, RLHF, IRL, and PbRL.

View on GitHub resources Resources on various topics being worked on at IvLabs. Reinforcement Learning Courses. In these courses, you will learn the foundations of Reinforcement Learning. RLlib Scalable Reinforcement Learning Blog PostsTutorials. RL Introduction to Deep Reinforcement Learning

Thank you very much for making these tutorials! They are awesome! However there seems to be a number of incompatibilitiesbugs in this notebook. I had to make the following modifications to get the notebook running on Tensorflow 1.0.0

Reinforcement Learning DQN Tutorial. Created On Mar 24, 2017 Last Updated Jun 16, 2025 Last Verified Nov 05, 2024. Author Adam Paszke. Mark Towers. This tutorial shows how to use PyTorch to train a Deep Q Learning DQN agent on the CartPole-v1 task from Gymnasium.. You might find it helpful to read the original Deep Q Learning DQN paper. Task

View on GitHub Practical Deep Reinforcement Learning. This is a practical resource that makes it easier to learn about and apply deep reinforcement learning. For practitioners and researchers, Practical RL provides a set of practical implementations of reinforcement learning algorithms applied on different environments, enabling easy