DeepMind's New AI Uses Game Theory to Trounce Humans in 'Stratego'

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DeepMind's New AI Uses Game Theory to Trounce Humans in 'Stratego'
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The 'DeepNash' AI had a 97% win rate against other models and an 84% win rate against top human players.

owned DeepMind, according to new research shared with Gizmodo, say they’ve created a new AI agent capable of playing Stratego at a “human expert level.” The AI, called DeepNash, won nearly all of the matches it played against other AI’s and had an

84% overall win rate when competing against human players in online games. DeepNash, which learned to master the game by playing against itself, was able to make complex decisions and consider tradeoffs in “extraordinary” ways previous AI systems couldn’t. While Stratego may not initially seem like the most obvious example for training an AI, the researchers say the game’s combination of longer-

term decision making and imperfect influx of imperfect information make it a unique test bed. The game is typically played by two players and involves both strategy and deception. Players each have their own “armies” made up of pieces each with their own respective values. Players win by either capturing an opponent’s flag or capturing all of their moveable pieces.All of those pieces with their different values result in an extremely large amount of possible moves and outcomes.

To win, DeepNash mixed both long term strategy and short term decision making like bluffing and taking chances. It’s rare that two of those things can be done at the same times so well by an AI agent. Stratego’s combination of long, strategic thinking and making decisions based onG/O Media may get a commission

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