Book Image

Artificial Intelligence with Python Cookbook

By : Ben Auffarth
Book Image

Artificial Intelligence with Python Cookbook

By: Ben Auffarth

Overview of this book

Artificial intelligence (AI) plays an integral role in automating problem-solving. This involves predicting and classifying data and training agents to execute tasks successfully. This book will teach you how to solve complex problems with the help of independent and insightful recipes ranging from the essentials to advanced methods that have just come out of research. Artificial Intelligence with Python Cookbook starts by showing you how to set up your Python environment and taking you through the fundamentals of data exploration. Moving ahead, you’ll be able to implement heuristic search techniques and genetic algorithms. In addition to this, you'll apply probabilistic models, constraint optimization, and reinforcement learning. As you advance through the book, you'll build deep learning models for text, images, video, and audio, and then delve into algorithmic bias, style transfer, music generation, and AI use cases in the healthcare and insurance industries. Throughout the book, you’ll learn about a variety of tools for problem-solving and gain the knowledge needed to effectively approach complex problems. By the end of this book on AI, you will have the skills you need to write AI and machine learning algorithms, test them, and deploy them for production.
Table of Contents (13 chapters)

Controlling a cartpole

The cartpole is a control task available in OpenAI Gym, and has been studied for many years. Although it is relatively simple compared to others, it contains all that we need in order to implement a reinforcement learning algorithm, and everything that we develop here can be applied to other, more complex learning tasks. It can also serve as an example of robotic manipulation in a simulated environment. The advantage of taking one of the less demanding tasks is that training and turnaround is quicker.

OpenAI Gym is an open source library that can help to develop reinforcement algorithms by standardizing a broad range of environments for agents to interact with. OpenAI Gym comes with hundreds of environments and integrations ranging from robotic control, and walking in 3D to computer games and self-driving cars: https://gym.openai.com/.

The cartpole task is depicted in the following screenshot of the OpenAI Gym environment and consists of moving a cart to the left...