Skip to Main Content
Advanced Deep Learning with Keras
book

Advanced Deep Learning with Keras

by Rowel Atienza, Neeraj Verma, Valerio Maggio
October 2018
Intermediate to advanced content levelIntermediate to advanced
368 pages
9h 20m
English
Packt Publishing
Content preview from Advanced Deep Learning with Keras

Chapter 9. Deep Reinforcement Learning

Reinforcement Learning (RL) is a framework that is used by an agent for decision-making. The agent is not necessarily a software entity such as in video games. Instead, it could be embodied in hardware such as a robot or an autonomous car. An embodied agent is probably the best way to fully appreciate and utilize reinforcement learning since a physical entity interacts with the real-world and receives responses.

The agent is situated within an environment. The environment has a state that can be partially or fully observable. The agent has a set of actions that it can use to interact with its environment. The result of an action transitions the environment to a new state. A corresponding scalar reward is ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Hands-On Neural Networks with Keras

Hands-On Neural Networks with Keras

Niloy Purkait
Deep Learning with Keras

Deep Learning with Keras

Antonio Gulli, Sujit Pal
Keras Deep Learning Cookbook

Keras Deep Learning Cookbook

Rajdeep Dua, Sujit Pal, Manpreet Singh Ghotra

Publisher Resources

ISBN: 9781788629416Supplemental Content