What happened
Researchers from Carnegie Mellon, MIT, NYU and Stanford trained an AI called Ataraxos that beat Pim Niemeijer, arguably the best Stratego player ever, 15 games to one with four draws, using just 16 GPUs and a few thousand dollars.
Why it matters
The win came in a game where most information stays hidden, which earlier AI systems couldn't handle reliably — suggesting the method may work for other problems with long stretches of uncertainty.
What to watch
The result hinges on whether one match against one player proves the approach generalizes. Watch whether the team releases more matches or faces other top players.
WHO IT HITSAI researchers and game-theory teams working on imperfect-information problems may take note, since the training cost was small enough to be replicated outside big labs. Tournament organizers for strategy games could also see elite human play challenged in ways previously seen in chess and Go.
Summaries like this, in your inbox every morning.
Stratego had long resisted computer mastery even as chess, Go, and poker fell to machines. Deep Blue beat Garry Kasparov in 1997, AlphaGo beat Lee Sedol in 2016, and poker bots have beaten professionals for years. DeepMind, despite its exceptional budget, couldn't build a machine to reliably beat the best Stratego players.
The challenge came from the game's structure. In Stratego, each player gets 40 pieces, and only collisions reveal identities. MIT computer scientist Gabriele Farina noted that Texas Hold'em has just 1,326 possible hands, but Stratego has more than a decillion possible setups. Games can easily last 2,000 moves, compared to about 40 in chess. Bluffing adds another layer: move a weak piece like a marshal to scare the opponent, but bluff too often and threats lose meaning.
NYU researcher Eugene Vinitsky pointed to the distinctive scale of hidden information unfolding over a long time. The win with 16 GPUs suggests smaller teams may now tackle similar problems, though whether this approach extends beyond Stratego remains to be seen.
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