AI beats Stratego’s greatest player, ending one of the last human strongholds in board games
An artificial intelligence system has defeated the world’s greatest Stratego player, ending one of the last human strongholds in board games. The milestone was achieved by DeepNash, an AI from DeepMind that mastered the game’s hidden information.
DeepNash played against Vincent “Rookie” Hepp, the top-ranked human player. The AI won the head-to-head matches, demonstrating a profound understanding of bluffing and deduction.
The Last Human Stronghold
Stratego was considered one of the last bastions of human supremacy. This is because it is an “imperfect information” game.
Players cannot see every piece. Unlike chess, pieces are hidden. This forces players to rely on memory, deduction, and psychology.
Bluffing and deception are essential. A player must guess the opponent’s strategy and plan accordingly. This was thought to be uniquely human.
How DeepNash Succeeded
DeepMind’s AI used a novel algorithm called R-NaD, or Regularized Nash Dynamics. This allowed it to find a balanced, unexploitable strategy.
“DeepNash finds a strategy that cannot be easily beaten, regardless of the opponent’s actions,” the researchers explained.
The AI played millions of games against itself to learn. It developed a style that was simultaneously aggressive and cautious.
It learned to sacrifice pieces for information. This is a high-risk strategy that human players sometimes use, but DeepNash mastered it perfectly.
Why This Matters
The research goes beyond games. The techniques used to solve Stratego have real-world applications.
Negotiation and auctions involve hidden information and bluffing. AI can now model these scenarios better.
Cybersecurity is a game of imperfect information. Defenders hide their systems, and attackers hide their identity.
“This technology could be used to improve decision-making in any field where information is incomplete,” the developers noted.
The victory closes a chapter on human superiority in board games. It opens a new chapter for applying AI to complex, real-world deception.
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