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Hands-On Intelligent Agents with OpenAI Gym - Your guide to developing AI agents using deep reinforcement learning (Paperback)
Loot Price: R1,087
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Hands-On Intelligent Agents with OpenAI Gym - Your guide to developing AI agents using deep reinforcement learning (Paperback)
Expected to ship within 10 - 15 working days
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Implement intelligent agents using PyTorch to solve classic AI
problems, play console games like Atari, and perform tasks such as
autonomous driving using the CARLA driving simulator Key Features
Explore the OpenAI Gym toolkit and interface to use over 700
learning tasks Implement agents to solve simple to complex AI
problems Study learning environments and discover how to create
your own Book DescriptionMany real-world problems can be broken
down into tasks that require a series of decisions to be made or
actions to be taken. The ability to solve such tasks without a
machine being programmed requires a machine to be artificially
intelligent and capable of learning to adapt. This book is an
easy-to-follow guide to implementing learning algorithms for
machine software agents in order to solve discrete or continuous
sequential decision making and control tasks. Hands-On Intelligent
Agents with OpenAI Gym takes you through the process of building
intelligent agent algorithms using deep reinforcement learning
starting from the implementation of the building blocks for
configuring, training, logging, visualizing, testing, and
monitoring the agent. You will walk through the process of building
intelligent agents from scratch to perform a variety of tasks. In
the closing chapters, the book provides an overview of the latest
learning environments and learning algorithms, along with pointers
to more resources that will help you take your deep reinforcement
learning skills to the next level. What you will learn Explore
intelligent agents and learning environments Understand the basics
of RL and deep RL Get started with OpenAI Gym and PyTorch for deep
reinforcement learning Discover deep Q learning agents to solve
discrete optimal control tasks Create custom learning environments
for real-world problems Apply a deep actor-critic agent to drive a
car autonomously in CARLA Use the latest learning environments and
algorithms to upgrade your intelligent agent development skills Who
this book is forIf you're a student, game/machine learning
developer, or AI enthusiast looking to get started with building
intelligent agents and algorithms to solve a variety of problems
with the OpenAI Gym interface, this book is for you. You will also
find this book useful if you want to learn how to build deep
reinforcement learning-based agents to solve problems in your
domain of interest. Though the book covers all the basic concepts
that you need to know, some working knowledge of Python programming
language will help you get the most out of it.
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