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| I feel like it should be relatively easy to make a computer program that can learn the rules of Mao without knowing them to begin with. There has to be some feedback: a player gets penalties if he breaks the rules. This can be used to write a self-learning algorithm. | | I feel like it should be relatively easy to make a computer program that can learn the rules of Mao without knowing them to begin with. There has to be some feedback: a player gets penalties if he breaks the rules. This can be used to write a self-learning algorithm. |
− | : The tricky part is that rules in Mao aren't limited to a function that states whether or not you can play a card based on the cards already played. Rules can be about how you play the card, how you sit, what you say, what you do if you play a certain card, etc. Rules can also apply out of turn. You could be required to do something in reaction to another player doing something (e.g. congratulate a player if they play a King), or penalised for e.g. speaking to the player whose turn it currently is. In order for a computer to compete successfully, it would need to ingest a lot of peripheral information and run some sophisticated learning that accounts for far more than simply the state of the cards. Particularly within a regular group of players, there are rules that will be reused a lot, e.g. certain cards acting as Uno special cards, but there is no guarantee these will appear and players can make up arbitrary rules. --Tom
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− | Sorry, but I just undid a new editor's addition of the text (for Snakes And Ladders) of "except that as the game has to be played on software so that an AI can participate, a (pseudo)-random number generator takes the place of physical dice in dictating players' movement, making it no longer truly random. Also, while physical snakes-and-ladders boards are fixed in their design, the graphical representation of these boards can be altered at will." - Firstly because it was bullet-point-added, when it wasn't really supposed to be, but then I decided it needed much more editing than I thought worthwhile. To bullet my thoughts, though:
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− | * See the Beer Pong example for "AI in reality",
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− | * Even if there's not a robot arm shaking a physical dice (which is pseudorandom itself, at least in a Newtonian perspective, but tends to be Ok) as long as the supposed-PRNG is not controlled/filtered by the AI then it's perfectly valid for use,
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− | * Machine-vision is a thing. I'm sure there's a trivial way to make a generalised board-image-decoder to get around the artistic differences (possibly even machine learning, to make actual use of the AI).
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− | ....The main issue is that solving all these 'problems' leaves little for the backend 'gameplay and strategy' AI to do, as it must just pursue the path to victory (or not) that the dice/whatever formulaically dictate. So I want to honour the edit by mentioning it, but ultimately decided it should be undone. Pending perhaps a different approach to it, if anyone decides I was not fair (or correct) in my decision to do it this way. [[Special:Contributions/172.70.162.147|172.70.162.147]] 13:09, 12 February 2022 (UTC)
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− | If Snakes and Ladders and Seven Minutes in Heaven are mentioned, why not [[wikipedia:Game of Life|Game of Life]]? --[[Special:Contributions/162.158.159.132|162.158.159.132]] 17:24, 3 March 2024 (UTC)
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− | :That's (as I suspected) a disambiguation page, making me still wonder whether you mean {{w|Conway's Game of Life}} (which is a bit open-ended) or ''{{w|The Game of Life}}'' (which, if I remember the gameplay well enough is basically going to be the same luck-based-'challenge' as Snakes And Ladders with an expanded set of thematic bells-and-whistles added).
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− | :Such a confluence of names, however, makes me want to suggest {{w|Mastermind (board game)}} (well within 'solved' for just brute-force logic) or {{w|Mastermind (British game show)}} (you'd definitely need a Watson-level AI, though you probably you could zhoosh it up with a ChatGPT front-end). [[Special:Contributions/172.71.242.160|172.71.242.160]] 19:04, 3 March 2024 (UTC)
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