You're reading from TensorFlow 2 Reinforcement Learning Cookbook

Product typeBook

Published inJan 2021

Reading LevelExpert

PublisherPackt

ISBN-139781838982546

Edition1st Edition

Languages

Python

Tools

TensorFlow

Concepts

Reinforcement Learning

Author (1)

Palanisamy P

Training RL agents using a remote simulator service

In this recipe, we will look at how we can utilize a remote simulator service to train our agent. We will be reusing the SAC agent implementation from one of the previous chapters and will focus on how we can train the SAC, or any of your RL agents for that matter, using an RL simulator that is running elsewhere (on the cloud, for example) as a service. We will leverage the tradegym server we built in the previous recipe to provide us with the RL simulator service for this recipe.

Let’s get started!

Getting ready

To complete this recipe, and to ensure that you have the latest version, you will first need to activate the tf2rl-cookbook Python/conda virtual environment. Make sure to update the environment to match the latest conda environment specification file (tfrl-cookbook.yml) in the cookbook’s code repository. If the following import statements run without issues, you are ready to get started:

import datetime...

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TensorFlow 2 Reinforcement Learning Cookbook

Published in: Jan 2021Publisher: PacktISBN-13: 9781838982546

Author (1)

Palanisamy P

Praveen Palanisamy works on developing autonomous intelligent systems. He is currently an AI researcher at General Motors R&D. He develops planning and decision-making algorithms and systems that use deep reinforcement learning for autonomous driving. Previously, he was at the Robotics Institute, Carnegie Mellon University, where he worked on autonomous navigation, including perception and AI for mobile robots. He has experience developing complete, autonomous, robotic systems from scratch.
Read more about Palanisamy P

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You're reading from TensorFlow 2 Reinforcement Learning Cookbook

Training RL agents using a remote simulator service

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Unlock this book and the full library FREE for 7 days

Author (1)

Hands-On Intelligent Agents with OpenAI Gym

TensorFlow Reinforcement Learning Quick Start Guide

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Hands-On Reinforcement Learning with Python

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