AI Algorithms for Gaming
With Eduardo Corpeño
Liked by 621 users
Duration: 2h 5m
Skill level: Advanced
Released: 4/10/2020
Course details
In 1997, an IBM computer named Deep Blue beat Gerry Kasparov, a world chess champion, after a six-game match. While AI technology has grown in exciting, and often revolutionary, ways since Deep Blue's victory at the chessboard in the late 90s, many of the techniques it implemented are still relevant today. In this course, explore some of these techniques as you learn how to leverage key AI algorithms to create two-player, turn-based games that are challenging enough to keep players guessing. Instructor Eduardo Corpeño covers using the minimax algorithm for decision-making, the iterative deepening algorithm for making the best possible decision by a deadline, and alpha-beta pruning to improve the running time, among other clever approaches. Plus, he gives you a chance to try out these techniques yourself as he steps through the development of a cat trap game using Python.
Skills you’ll gain
Meet the instructor
Learner reviews
-
Khaled_M_Ali Aklan Albanna
Khaled_M_Ali Aklan Albanna
I.T. Consultant at YBRD | Intelligent systems developer and analyst
-
Hüseyin Can Çelikkol
Hüseyin Can Çelikkol
Student in Karadeniz Technical University. Artificial Intelligence enthusiast
-
Andrey Ermishin
Andrey Ermishin
Data Scientist Python developer (Pandas,Sklearn,TensorFlow,PyTorch), Algorithms, Git, SQL.
Contents
What’s included
- Practice while you learn 1 exercise file
- Learn on the go Access on tablet and phone
Download courses
Use your iOS or Android LinkedIn Learning app, and watch courses on your mobile device without an internet connection.