Artificial Intelligence: Minimax Algorithm

在本次人工智能课程中，我们将实现 Minimax 算法及其优化版本，Alpha Beta 剪枝算法。我们将把算法应用到井字游戏中，创造一个无法被打败的人工智能。该算法将以通用方式实现，因此可以轻松应用于其他游戏。本课程面向希望将人工智能添加到游戏中的开发人员、希望实现 Minimax 算法的开发人员以及学生和人工智能爱好者。本课程还旨在成为人工智能、机器学习和深度学习等更高级课程的垫脚石。本课程使用 Python 编程语言教授，需要基本的编程技能。如果你没有所需的基础，我建议通过参加编程速成课程来加快速度（如果您愿意，我会在 Udemy 上提供 Python 编程速成课程）。涵盖的概念： Minimax 算法及其在 Python 中的实现 Alpha-beta 剪枝算法及其在 Python 中的实现 视频游戏中的人工智能 人工智能模块和框架的创建 启发式函数的概念 不要再等待进入人工智能的世界！

Published 7/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 703.08 MB | Duration: 1h 32m

Implementation of the Minimax algorithm (and Alpha-beta pruning) in Python

What you’ll learn
The minimax algorithm
The implementation of the Minimax algorithm in Python
The Alpha-Beta pruning algorithm
The implementation of the Alpha-Beta pruning algorithm in Python
Artificial intelligence in video games
Improving your Python knowledge through practice
Requirements
Basic programming knowledge
Description
In this artificial intelligence course, we will implement the Minimax algorithm and its optimized version, the Alpha Beta pruning algorithm. We will apply the algorithm to the tic-tac-toe game, creating an artificial intelligence which cannot be beaten. The algorithm will be implemented in a generic way, so that it can be easily applied to other games. This course is aimed at developers who would like to add artificial intelligence into their games, those who would like to implement the Minimax algorithm, as well as students and artificial intelligence enthusiasts. This course also aims to be a stepping stone to more advanced courses in artificial intelligence, machine learning and deep learning.This course, taught using the Python programming language, requires basic programming skills. If you don’t have the required foundation, I recommend getting up to speed by taking a crash course in programming (if you wouldd like, I offer a crash course in Python programming on Udemy). Concepts covered: The Minimax algorithm and its implementation in PythonThe Alpha-beta pruning algorithm and its implementation in PythonArtificial intelligence in video gamesThe creation of artificial intelligence modules and frameworksThe concept of heuristic functionsDo not wait any longer before jumping into the world of artificial intelligence!

Overview

Section 1: Introduction

Lecture 1 Introduction

Section 2: Minimax Algorithm

Lecture 2 Minimax Algorithm

Lecture 3 Pseudocode

Lecture 4 Generic API

Section 3: Implementation

Lecture 5 Minimax

Lecture 6 Game-state

Lecture 7 Tic Tac Toe

Lecture 8 User Interface (UI)

Lecture 9 Tests

Lecture 10 Finishing up

Section 4: Alpha-beta pruning & conclusion

Lecture 11 Alpha-beta pruning

Lecture 12 Conclusion

For those who want to learn the Minimax algorithm,For developers who want to introduce artificial intelligence into their games,For those who are interested in artificial intelligence