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Hands-On Reinforcement Learning with Python

You're reading from  Hands-On Reinforcement Learning with Python

Product type Book
Published in Jun 2018
Publisher Packt
ISBN-13 9781788836524
Pages 318 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Sudharsan Ravichandiran Sudharsan Ravichandiran
Profile icon Sudharsan Ravichandiran
LinkedIn
Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.
See other products by Sudharsan Ravichandiran

Table of Contents (16) Chapters

Preface Introduction to Reinforcement Learning Getting Started with OpenAI and TensorFlow The Markov Decision Process and Dynamic Programming Gaming with Monte Carlo Methods Temporal Difference Learning Multi-Armed Bandit Problem Deep Learning Fundamentals Atari Games with Deep Q Network Playing Doom with a Deep Recurrent Q Network The Asynchronous Advantage Actor Critic Network Policy Gradients and Optimization Capstone Project – Car Racing Using DQN Recent Advancements and Next Steps Assessments Other Books You May Enjoy

Chapter 10

  1. A3C is the Asynchronous Advantage Actor Critic network which uses several agents to learn parallel.
  2. Three A's are Asynchronous, Advantage, Actor Critic.
  3. A3C requires less computation power and training time than DQN.
  4. All agents (workers) works in copies of the environment and then global network aggregate their experience.
  5. Entropy is used to ensure enough exploration.
  6. Refer section How A3C works.
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Authors (1)

Profile icon Sudharsan Ravichandiran
LinkedIn
Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.
See other products by Sudharsan Ravichandiran

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