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

Game AI with the Minmax Algorithm and Alpha-Beta Pruning

In the first two topics, we saw how hard it was to create a winning strategy for a simple game such as Tic-Tac-Toe. The last topic introduced a few structures for solving search problems with the A* algorithm. We also saw that tools such as the simpleai library help us reduce the effort we put in to describe a task with code.

We will use all of this knowledge to supercharge our game AI skills and solve more complex problems.

Search Algorithms for Turn-Based Multiplayer Games

Turn-based multiplayer games such as Tic-Tac-Toe are similar to pathfinding problems. We have an initial state, and we have a set of end states, where we win the game.

The challenge with turn-based multiplayer games is the combinatoric explosion of the opponent's possible moves. This difference justifies treating turn-based games differently than a regular pathfinding problem.

For instance, in the Tic-Tac-Toe game, from an empty board, we can select one of the nine...