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)

Summary

In this chapter, we explored the list of Gym environments available on your system, which you installed in the previous chapter, and then understood the naming conventions, or nomenclature, of the environments. We then revisited the agent-environment interaction (the RL loop) diagram and understood how the Gym environment provides the interfaces corresponding to each of the arrows we saw in the image. We then looked at a consolidated summary of the four values returned by the Gym environment's step() method in a tabulated, easy-to-understand format to reinforce your understanding of what they mean!

We also explored in detail the various types of spaces used in the Gym for the observation and action spaces, and we used a script to print out what spaces are used by an environment to understand the Gym environment interfaces better. In our next chapter, we will consolidate...