Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning

Re:Mastering the Game of Stratego with Model-Free Multiagent... by spywaregorilla on Monday July 11, 2022 @09:35PM (#32064524)

> This actually does seem to be bad intuition to me, because your intuitive explanation isn't being expressed in terms of strategies. You wouldn't want to "attack this frontline unit" but would want to have a probability distribution over your potential options. This is similar how you wouldn't want to "play rock" in RPS, but would instead want to play {R: 1/3, P: 1/3, S: 1/3}.

My point is that your decision to attack is one that takes 3-5 turns with no meaningful possible positional maneuvering. So a game may have 200 turns but many fewer "decisions". There's not much "area control" like in many other strategic boardgames. It's more bluffing about your original setup choices. Every battle is reduced to a bet of whether your unit is higher or not and if it is, well you don't have a lot of agency on that. Especially if attacking.

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Re:Mastering the Game of Stratego with Model-Free Multiagent... by TemplateRex on Tuesday July 12, 2022 @12:29PM (#32072309)

It's true that many move sequences can be collapsed to a single maneuver. However, the area control remark is inaccurate: controlling or occupying the 3 alleys is very important and requires careful positional play. Getting the right "lane parity" to attack pieces frontally is crucial here, as is pincer movements around the lake with multiple power pieces. You seem to view Stratego as a superficial and repetitive game, but high level play goes considerable beyond a few bluffs and mechanical exchanges.

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