Packt+ | Advance your knowledge in tech

All Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Reinforcement Learning with TensorFlow

You're reading from Reinforcement Learning with TensorFlow

Product type Book

Published in Apr 2018

Publisher Packt

ISBN-13 9781788835725

Pages 334 pages

Edition 1st Edition

Languages

Concepts

Reinforcement Learning

Author (1):

Sayon Dutta

Table of Contents (21) Chapters

Title Page

Packt Upsell

Contributors

Preface

1. Deep Learning – Architectures and Frameworks

2. Training Reinforcement Learning Agents Using OpenAI Gym

3. Markov Decision Process

4. Policy Gradients

5. Q-Learning and Deep Q-Networks

6. Asynchronous Methods

7. Robo Everything – Real Strategy Gaming

8. AlphaGo – Reinforcement Learning at Its Best

9. Reinforcement Learning in Autonomous Driving

10. Financial Portfolio Management

11. Reinforcement Learning in Robotics

12. Deep Reinforcement Learning in Ad Tech

13. Reinforcement Learning in Image Processing

14. Deep Reinforcement Learning in NLP

1. Further topics in Reinforcement Learning

2. Other Books You May Enjoy

Leave a review - let other readers know what you think

Index

Temporal difference rule

Firstly, temporal difference (TD) is the difference of the value estimates between two time steps. It is different from the outcome-based Monte Carlo approach where a full look ahead till the end of the episode is done in order to update the learning parameters. In case of temporal difference learning, only one step look ahead is done and a value estimate of the state at the next step is used to update the current state's value estimate. Thus, learning parameters update along the way. Different rules to approach temporal difference learning are the TD(1), TD(0), and TD(

) rules. The basic notion in all the approaches is that the value estimate of the next step is used to update the current state's value estimate.

TD(1) rule

TD(1) incorporates the concept of eligibility trace. Let's go through the pseudo code of the approach and then we will discuss it in detail:

Episode T
    For all s, At the start of the episode : e(s) = 0 and 
        After  : (at step t)


     ...

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at €14.99/month. Cancel anytime

Authors (1)

Sayon Dutta

Sayon Dutta is an Artificial Intelligence researcher and developer. A graduate from IIT Kharagpur, he owns the software copyright for Mobile Irrigation Scheduler. At present, he is an AI engineer at Wissen Technology. He co-founded an AI startup Marax AI Inc., focused on AI-powered customer churn prediction. With over 2.5 years of experience in AI, he invests most of his time implementing AI research papers for industrial use cases, and weightlifting.

See other products by Sayon Dutta

Other recommended products

Related to this chapter

Hands-On Reinforcement Learning with Python

Hands-On Reinforcement Learning with Python

Reinforcement learning is a self-evolving type of machine learning that takes us closer to achieving true artificial intelligence. This easy-to-follow guide explains everything from scratch using rich examples written in Python.

Jun 2018 10 hours 36 minutes

Hands-On Intelligent Agents with OpenAI Gym

Hands-On Intelligent Agents with OpenAI Gym

Walks through the hands-on process of building intelligent agents from the basics and all the way up to solving complex problems including playing Atari games and driving a car autonomously in the CARLA simulator. Discusses various learning environments and how to transform real-world problems into learning environments and solve using the agents.

Jul 2018 8 hours 28 minutes

TensorFlow Reinforcement Learning Quick Start Guide

TensorFlow Reinforcement Learning Quick Start Guide

This book is an essential guide for anyone interested in Reinforcement Learning. The book provides an actionable reference for Reinforcement Learning algorithms and their applications using TensorFlow and Python. It will help readers leverage the power of algorithms such as Deep Q-Network (DQN), Deep Deterministic Policy Gradients (DDPG), and Proximal Policy Optimization (PPO) to solve challenging control and decision-making problems.

Mar 2019 6 hours 8 minutes

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python - Second Edition will help you learn reinforcement learning algorithms, techniques and architectures – including deep reinforcement learning – from scratch. This new edition is an extensive update of the original, reflecting the state-of-the-art latest thinking in reinforcement learning.

Sep 2020 25 hours 20 minutes

Hands-On Q-Learning with Python

Hands-On Q-Learning with Python

Q-learning is the reinforcement learning approach behind Deep-Q-Learning and is a values-based learning algorithm in RL. This book will help you get comfortable with developing the effective agents for Q learning and also make you learn to effectively develop and deploy Deep Q networks for complex AI applications.

Apr 2019 7 hours 4 minutes

Python Reinforcement Learning Projects

Python Reinforcement Learning Projects

Python Reinforcement Learning Projects brings various aspects and methodologies of RL using 8 real-world projects that explore RL and will have hands-on experience with real data and artificial intelligence problems. You will learn to build self-learning models using sophisticated techniques like Q-learning, Markov models and Monte-Carlo process.

Sep 2018 9 hours 52 minutes

PyTorch 1.x Reinforcement Learning Cookbook

PyTorch 1.x Reinforcement Learning Cookbook

This book presents practical solutions to the most common reinforcement learning problems. The recipes in this book will help you understand the fundamental concepts to develop popular RL algorithms. You will gain practical experience in the RL domain using the modern offerings of the PyTorch 1.x library.

Oct 2019 11 hours 20 minutes

TensorFlow 2 Reinforcement Learning Cookbook

TensorFlow 2 Reinforcement Learning Cookbook

This cookbook will help you to gain a solid understanding of deep reinforcement learning (RL) algorithms with the help of concise, easy-to-follow implementations from scratch. You'll learn how to implement these algorithms with minimal code and develop AI applications to solve real-world and business problems using RL.

Jan 2021 15 hours 44 minutes

Practical Reinforcement Learning

Practical Reinforcement Learning

Reinforcement learning (RL) is becoming a popular tool for constructing autonomous systems that improve themselves with experience. We will break the RL framework into its core building blocks, and provide you with details of each element. This book is divided into three parts. The first part defines Reinforcement Learning and describes the basics and the Python and Java frameworks, which we are going to use later in the book. The second part discusses learning techniques with basic algorithms such as Temporal Difference, Monte Carlo, and Policy Gradient—all with practical examples. Lastly, in the third part we apply Reinforcement Learning with the most recent and widely used algorithms, via practical applications.

Oct 2017 11 hours 12 minutes

Reinforcement Learning Algorithms with Python

Reinforcement Learning Algorithms with Python

With this book, you will understand the core concepts and techniques of reinforcement learning. You will take a look into each RL algorithm and will develop your own self-learning algorithms and models. You will optimize the algorithms for better precision, use high-speed actions and lower the risk of anomalies in your applications.

Oct 2019 12 hours 12 minutes

The Reinforcement Learning Workshop

The Reinforcement Learning Workshop

With the help of practical examples and engaging activities, The Reinforcement Learning Workshop takes you through reinforcement learning’s core techniques and frameworks. Following a hands-on approach, it allows you to learn reinforcement learning at your own pace to develop your own intelligent applications with ease.

Aug 2020 27 hours 24 minutes

Mastering Reinforcement Learning with Python

Mastering Reinforcement Learning with Python

This book focuses on expert-level explanations and implementations of scalable reinforcement learning algorithms and approaches. Starting with the fundamentals, the book covers state-of-the-art methods from bandit problems to meta-reinforcement learning. You’ll also explore practical examples inspired by real-life problems from the industry.

Dec 2020 18 hours 8 minutes

Personalised recommendations for you

Based on your interests and search pattern

Ever wonder why speech recognition systems don't understand the Scottish accent, or what would happen if an astronaut only ate mac 'n' cheese, or other spurious reflections you'd have at a bar? We did, then collated those deliberations into absurd research articles with fake figures and methodologies inspired by even more fictionally absurd studies.

Aug 2023 7 hours 40 minutes

Generative AI with LangChain

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

Dec 2023 12 hours 0 minutes

Generative AI with LangChain

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

Dec 2023 12 hours 0 minutes

Generative AI with LangChain

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

Dec 2023 12 hours 0 minutes

Generative AI with LangChain

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

Dec 2023 12 hours 0 minutes

Mastering Tableau 2023

Mastering Tableau 2023

This book is a comprehensive resource to mastering your Tableau skills and becoming a BI expert. As you progress, you will learn how to build advanced dashboards and improve your storytelling to derive key business insight, as well as make you well-versed with advanced functionalities of Tableau in the business intelligence domain.

Aug 2023 22 hours 48 minutes

Building AI Applications with ChatGPT APIs

Building AI Applications with ChatGPT APIs

This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.

Sep 2023 8 hours 36 minutes

Building AI Applications with ChatGPT APIs

Building AI Applications with ChatGPT APIs

This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.

Sep 2023 8 hours 36 minutes

Data Engineering with AWS

Data Engineering with AWS

Embark on a journey to master data engineering pipelines on AWS! Our book offers a hands-on experience of AWS services for ingesting, transforming, and consuming data. Whether you're an absolute beginner or someone with basic data engineering experience, this guide is an indispensable resource.

Oct 2023 21 hours 12 minutes

Modern Data Architecture on AWS

Modern Data Architecture on AWS

Every organization wants an agile, performant, and cost-effective data platform that meets all their current and future business needs. Purpose-built AWS analytics services and their features play a big part in building such a modern data platform. This book brings to you all the design and architectural patterns that’ll help you achieve this goal.

Aug 2023 14 hours 0 minutes

Practical Guide to Applied Conformal Prediction in Python

Practical Guide to Applied Conformal Prediction in Python

Discover the power of Conformal Prediction with the "Practical Guide to Applied Conformal Prediction in Python." Master the latest techniques to quantify uncertainty in machine learning and computer vision models, and seamlessly apply them to your industry applications.

Dec 2023 8 hours 0 minutes

TinyML Cookbook

TinyML Cookbook

With over 70 project-based recipes, the TinyML Cookbook is a practical guide that will help you to get the most out of your microcontrollers. It provides a comprehensive understanding of the theoretical foundations while giving you hands-on experience training ML models for deployment on Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and SparkFun RedBoard Artemis Nano microcontrollers.

Nov 2023 22 hours 8 minutes