Publications and Related Research
The following links provide additional information about technologies used in GAR.
Publications
CIG Journal: Describes in detail cgNEAT and multiplayer procedural content generation in GAR. (coming soon)
CIG09 Conference Paper: Reveals the inner workings of GAR, focusing on initial single player content generation results. Best Paper Award CIG 2009.
AIIDE09 Demo Paper A short 2-page description with some images for the GAR demo at AIIDE 2009.
Evolving Particle Systems
The system of evolving particle systems in GAR is based on the techniques described in this paper.
CPPNs / ANNS
CPPNs, a form of ANN, power the weapons in the game.
IEC
IEC is a process through which evolutionary or genetic algorithms are guided by human input rather than traditional fitness functions. Weapons in the game evolve by a form of collaborative IEC.
NEAT
NEAT is a neuroevolution algorithm that evolves CPPNs and ANNs. The CPPNs that power the weapons in GAR are evolved by a special variant of NEAT called content-generating NEAT (cgNEAT)
Neuro-Evolving Robotic Operatives Game
NERO is another video game based on a variant of NEAT. NERO uses real-time NEAT (rtNEAT) to evolve the behaviors of robots in real-time. In NERO, players evolve robotic army AI by training them to complete objectives. Players can pit their trained armies against each other in a battle royale.
Particle Systems
Particle systems are the de-facto technology for creating effects such as fire, smoke, energy, explosions, and many other "fuzzy objects" in computer graphics and games. NEAT Particles is a predecessor to GAR that allows users to evolve particle systems through a simple interface.