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The DeepMind team notes that StarCraft 2 provides a rich test bed for AI research, particularly because it lacks a single best strategy.

Much of the gameplay map is initially concealed from players so that they’re forced to seek out their opponents’ moves, and throughout, players must balance short-term tasks like constructing buildings and controlling units with planning winning moves and managing resources.

Controllable worker units gather resources to build structures and create new technologies, which in turn unlock more sophisticated units and structures. StarCraft 2 players have the aforementioned three races from which to choose.

It plays on the official StarCraft 2 server using the same maps and conditions as human players, and it’s able to continuously self-improve without human intervention, courtesy a combination of general-purpose machine learning techniques including self-play via reinforcement learning, multi-agent learning, and imitation learning. It beat top player Grzegorz “MaNa” Komincz and teammate Dario “TLO” Wünsch in a series of 10 matches, but a paper today published in the journal Nature describes a more impressive feat: Further training boosted AlphaStar’s ranking above 99.8% of all active players and earned it the level of GrandMaster - a spot among the top 200 regional players - for all three StarCraft 2 player races (Protoss, Terran, and Zerg).ĭeepMind says this latest iteration of AlphaStar - AlphaStar Final - can play a full StarCraft 2 match under “professionally approved” conditions, importantly with limits on the frequency of its actions and by viewing the world through a game camera.

Learn more about what comes next.Īlphabet subsidiary DeepMind - which famously developed AlphaZero, a machine learning system that bested world champions in chess, shogi, and Go - returned to the video game domain once again in January with AlphaStar, which tackled Activision Blizzard’s popular real-time strategy title StarCraft 2. Join gaming leaders online at GamesBeat Summit Next this upcoming November 9-10.