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TensorFlow 2 Reinforcement Learning Cookbook

You're reading from  TensorFlow 2 Reinforcement Learning Cookbook

Product type Book
Published in Jan 2021
Publisher Packt
ISBN-13 9781838982546
Pages 472 pages
Edition 1st Edition
Languages
Author (1):
Palanisamy P Palanisamy P
Profile icon Palanisamy P
Toc

Table of Contents (11) Chapters close

Preface 1. Chapter 1: Developing Building Blocks for Deep Reinforcement Learning Using Tensorflow 2.x 2. Chapter 2: Implementing Value-Based, Policy-Based, and Actor-Critic Deep RL Algorithms 3. Chapter 3: Implementing Advanced RL Algorithms 4. Chapter 4: Reinforcement Learning in the Real World – Building Cryptocurrency Trading Agents 5. Chapter 5: Reinforcement Learning in the Real World – Building Stock/Share Trading Agents 6. Chapter 6: Reinforcement Learning in the Real World – Building Intelligent Agents to Complete Your To-Dos 7. Chapter 7: Deploying Deep RL Agents to the Cloud 8. Chapter 8: Distributed Training for Accelerated Development of Deep RL Agents 9. Chapter 9: Deploying Deep RL Agents on Multiple Platforms 10. Other Books You May Enjoy

Packaging Deep RL agents for cross-platform deployment

Although the grandest success of Deep RL has been in the domain of game playing (Atari, Chess, Go, Shogi) and simulated robotics, real-world applications are starting to emerge where Deep RL agents show a lot of promise and value. Deploying Deep RL agents to a variety of physical form factors such as embedded controllers, computers, autonomous cars, drones, and other robots, and so on is expected soon. Differences in hardware processors (CPU, GPU, TPU, FPGA, ASIC), operating systems (Linux, Windows, OSX, Android), architectures (x86, ARM), and form factors (server, desktop, mobile, IoT, embedded systems, and so on) make the deployment process challenging. This recipe includes guidelines around how you can leverage the TensorFlow 2.x framework's ecosystem of libraries, tools, and utilities to package Deep RL agent models suitable for deployments to the web, mobile, IoT, embedded systems, robots, and desktop platforms.

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