Screaming racers: Competitive autonomous drivers for racing games

Online videogames are not just entertainment products but also can be used as environments for Multi-agent Systems (MAS) where agents can reach multiple sources of knowledge from which to learn. In particular, videogames are especially well suited for learning Human-Level Artificial Intelligence, because they strengthen human-agent interaction. In this paper we present Screaming Racers, a simple car-racing online videogame designed to experiment with MAS which learn to drive racing cars along competition tracks. We also present our car-driving learning results with several Neuroevolution techniques, including Neuroevolution of Augmenting Topologies (NEAT).