Deep RL Book Choice

Deep RL Book Choice : r/reinforcementlearning - Reddit

I need a book reccomendation. I was going to start off with Sutton and Barto, but I heard it doesn't cover Deep Reinforcement Learning.

Textbooks (or other sources) on deep reinforcement learning which ...

For me was "The Art of Reinforcement Learning" by Michael Hu the best book so far. On the other side I found the Sutton and Barto Book extremely ...

Grokking Deep Reinforcement Learning - Manning Publications

Grokking Deep Reinforcement Learning uses engaging exercises to teach you how to build deep learning systems. This book combines annotated Python code with ...

Resources for Deep Reinforcement Learning | by Yuxi Li - Medium

This is a collection of resources for deep reinforcement learning, including the following sections: Books, Surveys and Reports, Courses, Tutorials and Talks, ...

What is the best online course and book for deep reinforcement ...

For (shallow) reinforcement learning, the course by David Silver (mentioned in the previous answers) is probably the best out there.

Best Reinforcement Learning Books with Practical Examples

This book is a practical and accessible guide to deep reinforcement learning (DRL), which is a combination of RL and deep learning. It is ...

stevenschmatz/deep-rl-book: A book on deep reinforcement learning

Prerequisites · Reinforcement Learning: An Introduction, Sutton & Barto, 2nd edition. This book is the most famous textbook in RL. · Deep Learning, Goodfellow, ...

Reinforcement Learning: An Introduction Richard S. · Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy ...

Could you recommend a reinforcement learning reading list ... - Quora

1. Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville · 2. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by ...

Deep Reinforcement Learning in Action - book review

What did I think about the book? · dynamic programming · multi-arm bandit · constructing a DQN in PyTorch · counteracting catastrophic forgetting ...

On Choosing a Deep Reinforcement Learning Library - Dataiku Blog

Consequently, a lot of deep reinforcement learning libraries have been developed and it can be hard to choose the best library. We had this ...

20 Best Deep Reinforcement Learning Books of All Time

In the past decade deep RL has achieved remarkable results on a range of problems, from single and multiplayer games–such as Go, Atari games, and DotA 2–to ...

Deep Reinforcement Learning Hands-On | Data | Subscription - Packt

Key benefits · Learn with concise explanations, modern libraries, and diverse applications from games to stock trading and web navigation · Develop deep RL models ...

Reinforcement Learning Books | Restackio

1. Reinforcement Learning: An Introduction by Richard S. · 2. Deep Reinforcement Learning Hands-On by Maxim Lapan · 3. Algorithms for ...

Reinforcement Learning, by the Book - YouTube

... Deep Reinforcement Learning Doesn't Work Yet, 2018, https://www.alexirpan.com/2018/02/14/rl-hard.html [6] D. Silver, et al., Mastering Chess ...

Deep Reinforcement Learning | SpringerLink

Softcover Book USD 15.99 USD 54.99. Discount applied Price excludes VAT (USA) ; Discount applied Price excludes VAT (USA) ; About the author. Aske Plaat is a ...

Part 1: Key Concepts in RL — Spinning Up documentation

The two most common kinds of stochastic policies in deep RL are categorical policies and diagonal Gaussian policies. Categorical policies can be used in ...

Deep Reinforcement Learning: Frontiers of Artificial Intelligence

This book starts with the basics on Reinforcement Learning using very ... Your privacy, your choice. We use essential cookies to make sure the site can ...

Overview of Deep Reinforcement Learning Methods - YouTube

... book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Brunton and Kutz Book Website: http ...

Solving Continual Combinatorial Selection via Deep Reinforcement ...

In this paper, we present a deep RL algorithm to solve this issue by adopting the following key ideas. First, we convert the original S-MDP into an Iterative ...