Title

Demonstrating Automatic Content Generation In The Galactic Arms Race Video Game

Abstract

In most modern video games, content (e.g. models, levels, weapons, etc.) shipped with the game is static and unchanging, or at best, randomized within a narrow set of parameters. However, if game content could be constantly renewed, players would remain engaged longer. To realize this ambition, the content-generating NeuroEvolution of Augmenting Topologies (cgNEAT) algorithm automatically evolves novel game content based on player preferences, as the game is played. To demonstrate this approach, the Galactic Arms Race (GAR) video game, which incorporates cgNEAT, will be presented. In GAR, players pilot space ships and fight enemies to acquire novel particle system weapons that are evolved by the game. The live demo will show how GAR players can discover a wide variety of weapons that are not only novel, but also based on and extended from previous content that they preferred in the past. The implication of cgNEAT is that it is now possible to create games that generate their own content, potentially signicantly reducing the cost of content creation and increasing the replay value of games.© 2009, Association for the Advancement of Artificial.

Publication Date

12-1-2009

Publication Title

Proceedings of the 5th Artificial Intelligence and Interactive Digital Entertainment Conference, AIIDE 2009

Number of Pages

189-190

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

84883057533 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84883057533

This document is currently not available here.

Share

COinS