Book Image

Artificial Intelligence and Machine Learning Fundamentals

By : Zsolt Nagy
Book Image

Artificial Intelligence and Machine Learning Fundamentals

By: Zsolt Nagy

Overview of this book

Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples. As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law. By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills!
Table of Contents (10 chapters)
Artificial Intelligence and Machine Learning Fundamentals

Pathfinding with the A* Algorithm

In the first two topics, we learned how to define an intelligent agent, and how to create a heuristic that guides the agent toward a desired state. We learned that this was not perfect, because at times we ignored a few winning states in favor of a few losing states.

We will now learn a structured and optimal approach so that we can execute a search for finding the shortest path between the current state and the goal state: the A* ("A star" instead of "A asterisk") algorithm:

Figure 2.3: Finding the shortest path in a maze

For a human, it is simple to find the shortest path, by merely looking at the image. We can conclude that there are two potential candidates for the shortest path: route one starts upwards, and route two starts to the left. However, the AI does not know about these options. In fact, the most logical first step for a computer player would be moving to the square denoted by the number 3 in the following diagram:

Why? Because this is the only...