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)

What is an intelligent agent?

A major goal of artificial intelligence is to build intelligent agents. Perceiving their environment, understanding, reasoning and learning to plan, and making decisions and acting upon them are essential characteristics of intelligent agents. We will begin our first chapter by understanding what an intelligent agent is, from the basic definition of agents, to adding intelligence on top of that.

An agent is an entity that acts based on the observation (perception) of its environment. Humans and robots are examples of agents with physical forms.

A human, or an animal, is an example of an agent that uses its organs (eyes, ears, nose, skin, and so on) as sensors to observe/perceive its environment and act using their physical body (arms, hands, legs, head, and so on). A robot uses its sensors (cameras, microphones, LiDAR, radar, and so on) to observe/perceive its environment and act using its physical robotic body (robotic arms, robotic hands/grippers, robotic legs, speakers, and so on).

Software agents are computer programs that are capable of making decisions and taking actions through interaction with their environment. A software agent can be embodied in a physical form, such as a robot. Autonomous agents are entities that make decisions autonomously and take actions based on their understanding of and reasoning about their observations of their environment.

An intelligent agent is an autonomous entity that can learn and improve based on its interactions with its environment. An intelligent agent is capable of analyzing its own behavior and performance using its observations.

In this book, we will develop intelligent agents to solve sequential decision-making problems that can be solved using a sequence of (independent) decisions/actions in a (loosely) Markovian environment, where feedback in the form of reward signals is available (through percepts), at least in some environmental conditions.