gar.eecs.ucf.edu
eplex.cs.ucf.edu

GAR is both a multiplayer online video game and an experiment in automatic content generation driven by player preferences. Unique game content, namely spaceship weapon systems, automatically evolves based on player behavior through a specialized algorithm called cgNEAT (content-generating NeuroEvolution of Augmenting Topologies). In particular, new variants of weapons that players like are continually created by the game itself. In this way, the game never stays the same. GAR is the first video game to demonstrate that critical content can evolve as the game is played to satisfy its players.  For an idea of what the game is like, think "Space Diablo", with real-time combat, cool particle system weapons, and RPG-style leveling and skill trees.


We wanted to demonstrate that unique AI technology can positively impact how video games are made.  We chose automatic content generation as the main focus because we believe that content is a major bottleneck in the industry today.  While most effort in AI in games has traditionally centered on NPC behavior, content generation may prove a most compelling alternative application for AI.


Galactic Arms Race generates its own content (in particular, weapons) through an evolutionary algorithm in real time while the game is played.  Players can constantly discover unique weapons spawned in the online galaxy, evolved through their past weapon preferences.  To our knowledge, GAR is the first demonstration that this principle can work in a multiplayer video game.


The game took about 12 months to complete the first release but the genesis of the cgNEAT AI and particle system evolution technologies stretches back as far as 10 years to the invention of the original NEAT algorithm. We are currently working on GAR version 1.2.


Before the game was even started, we spent about a year experimenting with evolving particle systems (for genetic art programs) to learn how they can be generated most effectively by an evolutionary algorithm.


Several interesting facts:

-GAR won the Best Paper Award at 2009 IEEE Symposium on Computational Intelligence in Games (CIG09) and was Editor's Pick for Best AI in an Independent Game at AIGameDev.com.

-GAR has been covered in a variety of online media sources including Slashdot and Le Monde.  

-Finally, Ken Stanley, who directed the development of GAR along with Erin Hastings, was also a leader on the NERO video game, another experimental game based on evolutionary technology.


In evolutionary computation, which is the subfield of AI that studies evolutionary algorithms, the term "arms race" has a special meaning. At the same time, collecting weapons in outer space is also literally an "arms race."  So the title of the game actually manages to describe two facets of the game at the same time.


GAR co-leads are Erin Hastings and Ken Stanley. Erin – Port Saint Lucie, FL
Ken – Newton, MA


Erin – Undergrad: University of Florida, Grad: University of Central Florida
Ken – Undergrad: University of Pennsylvania., Grad: University of Texas at Austin


Erin – Graphics and gaming related research for graduate work. A lot of mods and maps for Unreal Tournament. GAR is my first original game.
Ken – Long-time researcher in AI in games.  First major production was NERO in 2005.


The GAR team met in the Evolutionary Complexity Research Group at the University of Central Florida.  Ken Stanley is the research group leader and the rest of the team is current or former UCF students.


Erin – World of Warcraft, Call of Duty Modern Warfare , Rock Band 2, Castle Age
Ken – New Super Mario Bros. Wii


Erin – Most hours spent probably in Everquest or WoW.
Ken – Galactic Empire, an online multiplayer BBS game from around 1990.


Erin – Whack-A-Mole
Ken – Any game that simply exploits old ideas to make more money.


Erin – Super NES
Ken – ColecoVision


Erin – PC
Ken – Wii


Erin – AI Research.
Ken – AI Research.

Erin Hastings
Ken Stanley
Derick Janssen