Displaying 1 to 3 from 3 results

Hands-On-Reinforcement-Learning-With-Python - Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

  •    Jupyter

Reinforcement Learning with Python will help you to master basic reinforcement learning algorithms to the advanced deep reinforcement learning algorithms. The book starts with an introduction to Reinforcement Learning followed by OpenAI and Tensorflow. You will then explore various RL algorithms and concepts such as the Markov Decision Processes, Monte-Carlo methods, and dynamic programming, including value and policy iteration. This example-rich guide will introduce you to deep learning, covering various deep learning algorithms. You will then explore deep reinforcement learning in depth, which is a combination of deep learning and reinforcement learning. You will master various deep reinforcement learning algorithms such as DQN, Double DQN. Dueling DQN, DRQN, A3C, DDPG, TRPO, and PPO. You will also learn about recent advancements in reinforcement learning such as imagination augmented agents, learn from human preference, DQfD, HER and many more.

gail-tf - Tensorflow implementation of generative adversarial imitation learning

  •    Python

The trained model will save in ./checkpoint, and its precise name will vary based on your optimization method and environment ID. Choose the last checkpoint in the series. Note: The following hyper-parameter setting is the best that I've tested (simple grid search on setting with 1500 trajectories), just for your information.

ros2learn - ROS 2 enabled Machine Learning algorithms

  •    Python

This repository contains a number of ROS and ROS 2 enabled Artificial Intelligence (AI) and Reinforcement Learning (RL) algorithms that run in selected environments. Please refer to Install.md to install from sources.





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