1. Galactic Arms Race (GAR): Automatic Content Generation In a Multiplayer Online Video Game
author: Ratan Kumar Guha, School of Electrical Engineering and Computer Science, University of Central Florida
author: Erin J. Hastings, School of Electrical Engineering and Computer Science, University of Central Florida
published: June 20, 2009, recorded: May 2009, views: 4564
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
This video showcases a new AI algorithm called cgNEAT that automatically generates content in video games. To demonstrate this new technique, we created a near-commercial-quality game called Galactic Arms Race (GAR) in which the weapons systems are entirely invented by the game itself. The cgNEAT method, which is short for content-generating NeuroEvolution of Augmenting Topologies, evolves new weapons (which are controlled by artificial neural networks) by varying the most popular weapons of the past. In this way, an evolutionary process causes the algorithm to explore the space of weapons as the game is played, producing a never-ending supply of novel and functional content. The aim is to show that AI can be sophisticated enough to produce some of the content in games without the need for artists or programmers, by observing what players liked in the past. The video presents a montage of actual gameplay that demonstrates the surprising variety of compelling weapons invented by the game itself. It also explicates the underlying AI technology more through action than through words. For more information on GAR, which will be released this Spring, please visit: http://gar.eecs.ucf.edu.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !