Foundations of Deep Reinforcement Learning

By Laura Graesser, Wah Loon Keng,

Book cover of Foundations of Deep Reinforcement Learning: Theory and Practice in Python

Book description

The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice

Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has achieved remarkable results on a range of problems, from single…

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Why read it?

1 author picked Foundations of Deep Reinforcement Learning as one of their favorite books. Why do they recommend it?

Of course, this is not the obvious book to recommend for reinforcement learning, but if you are a beginner, then it’s a quick and easy place to start. It’s compact and gets straight into the main algorithms.

It has a good balance between theory and code and will get you up and running quickly.

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