Mastering the strategy, tactical understanding, and team play involved in multiplayer video games represents a critical challenge for AI research. In our latest paper, now published in the journal Science, we present new developments in reinforcement learning, resulting in human-level performance in Quake III Arena Capture the Flag. This is a complex, multi-agent environment and one of the canonical 3D first-person multiplayer games. The agents successfully cooperate with both artificial and human teammates, and demonstrate high performance even when trained with reaction times comparable to human players. Furthermore, we show how these methods have managed to scale beyond research Capture the Flag environments to the full game of Quake III Arena.
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An early test tournament with humans playing CTF with and against trained agents and other humans
