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Home/ Questions/Q 8674125
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Editorial Team
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Editorial Team
Asked: June 12, 20262026-06-12T19:37:45+00:00 2026-06-12T19:37:45+00:00

I want to develop a two player game with imperfect information – Stratego. The

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I want to develop a two player game with imperfect information – “Stratego”.

The game is “somewhat” like chess but initially we don’t know anything about the ranks of the opponent’s pieces. When a piece attacks or is attacked by some opponent’s piece, their ranks are revealed and the higher rank piece kills/captures the lower rank piece.
More detail on the game can be found here.

I did a little research. I read “Opponent Modeling in Stratego” by J.A. Stankiewicz. But I couldn’t find a complete tutorial on how to develop the game. I have successfully developed before a two player game – “Othello” a.k.a. Reversi, and I’m familiar with MINIMAX algorithm and alpha-beta pruning.

I found somewhere that Monte-Carlo Tree Search is also used in developing zero-sum two player games. Can it be used for games like stratego? Can I get a complete tutorial for the same?

Any other tutorial not involving Monte-Carlo Tree Search would also be useful 🙂

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  1. Editorial Team
    Editorial Team
    2026-06-12T19:37:46+00:00Added an answer on June 12, 2026 at 7:37 pm

    I think MCTS would have a difficult time in Stratego since the initial spreading function is so large while the best play is very dependent on the ground-truth of the game. That is to say, MCTS would, in the best case, give you a play that’s statistically good amongst all the possible variations of your opponent’s pieces, but the best next move is highly dependent on which particular variation they’ve chosen.

    I’m still developing a solid understanding of MCTS, but it seems to me that MCTS does not do well in games where multi-round deceptive play involving hidden information is important (poker, canonically, but stratego, I would say, also). In such games, you really need to develop a model of the other player(s) situation/strategy and MCTS by its nature is going to give you an answer that is statistically related to all trees, not just the ground-truth tree.

    MCTS works fine with games involving large amounts of chance (backgammon and other board games involving dice and many card games) and seems to me an excellent general-purpose solution that could be rapidly adopted to a large number of modern “European-style” board games. (The interesting thing with those is that although they involve “deceptive strategy” they generally involve relatively little hidden information.)

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