Forty years to the day since PAC-MAN first hit arcades in Japan, and went on to munch a path to global stardom, the retro classic has been reborn, delivered courtesy of AI.
Trained on 50,000 episodes of the game, a powerful new AI model created by NVIDIA Research, called NVIDIA GameGAN, can generate a fully functional version of PAC-MAN — without an underlying game engine. That means that even without understanding a game’s fundamental rules, AI can recreate the game with convincing results.
GameGAN is the first neural network model that mimics a computer game engine by harnessing generative adversarial networks, or GANs. Made up of two competing neural networks, a generator and a discriminator, GAN-based models learn to create new content that’s convincing enough to pass for the original.
“This is the first research to emulate a game engine using GAN-based neural networks,” said Seung-Wook Kim, an NVIDIA researcher and lead author on the project.
As an artificial agent plays the GAN-generated game, GameGAN responds to the agent’s actions, generating new frames of the game environment in real time.
GameGAN is authored by Sanja Fidler, Kim, NVIDIA researcher Jonah Philion, University of Toronto student Yuhao Zhou and MIT professor Antonio Torralba. The paper will be presented at the Computer Vision and Pattern Recognition in June.
Read the full story, 40 Years on, PAC-MAN Recreated with AI by NVIDIA Researchers, on the NVIDIA Corporate Blog.