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

TensorFlow Keras

Concepts

Reinforcement Learning

Author (1)

Sudharsan Ravichandiran

Chapter 2

conda create --name universe python=3.6 anaconda
With Docker, we can pack our application with its dependencies, which is called container, and we can simply run our applications on the server without using any external dependency with our packed Docker container.
gym.make(env_name)
from gym import envs
print(envs.registry.all())
OpenAI Universe is an extension of OpenAI Gym and it also provides various rich environments.
Placeholder is used for feeding external data whereas variable is used for holding values.

Everything in TensorFlow will be represented as a computational graph that consists of nodes and edges, where nodes are the mathematical operations, say addition, multiplication and so on, and edges are the tensors.
Computation graphs will only be defined; in order to execute the computation graph, we use TensorFlow sessions.

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Hands-On Reinforcement Learning with Python

Published in: Jun 2018Publisher: PacktISBN-13: 9781788836524

Author (1)

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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Author (1)

Deep Reinforcement Learning with Python

PyTorch 1.x Reinforcement Learning Cookbook

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