Book Image

Hands-On Intelligent Agents with OpenAI Gym

By : Palanisamy P
Book Image

Hands-On Intelligent Agents with OpenAI Gym

By: Palanisamy P

Overview of this book

Many 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.
Table of Contents (12 chapters)

Understanding the anatomy of Gym environments

Any Gym-compatible environment should subclass the gym.Env class and implement the reset and step methods and the observation_space and action_space properties and attributes. There is also the opportunity to implement other, optional methods that can add additional functionality to our custom environments. The following table lists and describes the other methods available:

Functionality description
The shape and type of the observations returned by the environment.
The shape and type of the actions accepted by the environment.
Routines to reset the environment at the start or end of an episode.
Routines that calculate the necessary information to advance the environment, simulation, or game to the next step. The routine includes applying the chosen action...