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Deep Reinforcement Learning with Python : With PyTorch, TensorFlow and OpenAI Gym /

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Deep reinforcement learning is a fast-growing discipline that is making a significant impact in fields of autonomous vehicles, robotics, healthcare, finance, and many more. This book covers deep reinforcement learning using deep-q learning and policy gradient models with coding exercise. You'll...

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Bibliographic Details
Main Author: Sanghi, Nimish (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Berkeley, CA : Apress : Imprint: Apress, 2021.
Edition:1st ed. 2021.
Subjects:
Artificial intelligence.
Python (Computer program language).
Artificial Intelligence.
Python.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Chapter 1: Introduction to Deep Reinforcement Learning
  • Chapter 2: Markov Decision Processes
  • Chapter 3: Model Based Algorithms
  • Chapter 4: Model Free Approaches
  • Chapter 5: Function Approximation
  • Chapter 6:Deep Q-Learning
  • Chapter 7: Policy Gradient Algorithms
  • Chapter 8: Combining Policy Gradients and Q-Learning
  • Chapter 9: Integrated Learning and Planning
  • Chapter 10: Further Exploration and Next Steps.