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

Product typeBook
Published inJun 2018
Reading LevelIntermediate
PublisherPackt
ISBN-139781788836524
Edition1st Edition
Languages
Python
Tools
TensorFlowKeras
Concepts
Reinforcement Learning
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Sudharsan Ravichandiran
Sudharsan Ravichandiran
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Sudharsan Ravichandiran

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.
Read more about Sudharsan Ravichandiran

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What is a Deep Q Network?

Before going ahead, first, let us just recap the Q function. What is a Q function? A Q function, also called a state-action value function, specifies how good an action a is in the state s. So, we store the value of all possible actions in each state in a table called a Q table and we pick the action that has the maximum value in a state as the optimal action. Remember how we learned this Q function? We used Q learning, which is an off-policy temporal difference learning algorithm for estimating the Q function. We looked at this in Chapter 5, Temporal Difference Learning.

So far, we have seen environments with a finite number of states with limited actions, and we did an exhaustive search through all possible state-action pairs for finding the optimal Q value. Think of an environment where we have a very large number of states and, in each state, we have...

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Hands-On Reinforcement Learning with Python
Published in: Jun 2018Publisher: PacktISBN-13: 9781788836524
© 2018 Packt Publishing Limited All Rights Reserved

Author (1)

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Sudharsan Ravichandiran

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.
Read more about Sudharsan Ravichandiran

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