Ancient Roman Board Game(ludus-coriovalli.web.app) |
Ancient Roman Board Game(ludus-coriovalli.web.app) |
> Using Alpha-Beta search agents — the same class of algorithm that powered early chess computers — the team ran 1,000 simulated rounds for each candidate ruleset, allowing one second of processing time per move. The AI tracked which lines on the board were used most frequently during play, generating detailed edge-usage statistics....
> Nine game configurations matched the wear criteria. All of them were blocking games, and the most frequently matching format was a four-versus-two game in which pieces start on the board. This site faithfully reproduces one of these AI-validated configurations.
I would say this is more "inspired by" Ancient Rome.
I imagine the incentives of having a crisp story for media consumption don’t help. I’d hope to read a lot more: “we’re missing the majority of the pieces to this puzzle. This represents our best guess given current evidence and methods.”
That being said, "We asked an AI..." is a special kind of uncertainty that goes above and beyond anything else Archaeologists do.
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"No written rules for this game survived antiquity. To reconstruct how the game may have been played, researchers turned to the Ludii General Game System — a comprehensive digital platform developed at Maastricht University that can model and simulate thousands of historic board games. The results were published in the journal Antiquity (Volume 100, Issue 409, 2025).
Using Alpha-Beta search agents — the same class of algorithm that powered early chess computers — the team ran 1,000 simulated rounds for each candidate ruleset, allowing one second of processing time per move. The AI tracked which lines on the board were used most frequently during play, generating detailed edge-usage statistics.
These statistics were then compared to the physical wear patterns on Object 04433. To account for human cognitive biases — such as right-handed players preferring to play on the right side of the board — the researchers applied symmetry transformations to the simulation results, maximising consistency between AI-generated play and the actual marks left by ancient players.
Nine game configurations matched the wear criteria. All of them were blocking games, and the most frequently matching format was a four-versus-two game in which pieces start on the board. This site faithfully reproduces one of these AI-validated configurations."
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It's interesting that they considered use-wear on found pieces as input for their AI. Still, this study made a lot of assumptions. I wouldn't be surprised if a different team could use the same methods and come up with a completely different result.
Eg much is not known about dinosaurs. Many things cannot be found in fossils (obligatory xkcd: https://xkcd.com/1747/)
How do you communicate what is unknown or what can't be known?
Your complaint is like complaining that a CS paper doesn't even mention that P = NP is still unknown, and that it just assumes that the best sorting methods are O(n log n). Some things are considered general knowledge in a field, and in archaeology one of those things is: all of this is a best guess given current evidence and methods.
The whole paper is full of citations to other work, which is full of citations to other work - all this work linked includes detailed reports of what was found where and what-else was there, people who do statistical analyisis of similar findings, people who ask questions like "what explanations can there be for it?", more importantly "what else would we find if X was true, if Y was true?". When new evidence arrives, people can and do go back and re-examine these things. Your random skepticism and all the questions you may ask have already been asked and addressed, and frankly: these archaeologist's conclusions carry far far far more believable weight than your half-assed skepticism.
Model and simulate based on what?
> Nine game configurations matched the wear criteria.
So their idea was to generate candidate rulesets, have AI try to figure out rational play, then see which pieces would be moved most often and match that to the forensic evidence?
Here's a tablebase analysis for a simple bear game I constructed a while back: https://emarzion.github.io/coqtbgen/
Are there other known ancient games that work like this?
I was thinking of them yesterday because I noticed one for sale in the antiquities shop in Andor, which brought up all sorts of Earth/Rome/Star Wars cannon questions.
A) make sure you get at least one hare to one of the central two spots (will always be possible) and camp it there. Keep your other hare moving around on your side.
B) the opponent will have to bring two hounds over to catch your other hare. To do this they will have to create a gap between the first and second hound in the middle spot above/below your camped hare. As soon as this happens, move your camped hare upwards.
It's pretty easy after that TBH. The AI has usual burnt a load of moves by that point and you have so many options from that position
There needs to be something to stop a deadlock. Like an element of luck for the hares?
Edit: Or, put a different way: Sometimes the rules to games are lost for a reason; they're not very good.
The videos on the game (and all his other videos) with Irving Finkel, a curator at the British museum, are spellbinding. He has the looks, manners and enthusiasm of an eccentric museum curator from central casting!
This is much more palatable and cool since they’re not just randomly guessing what the game can be like this article is
We tend to just drape a bounding skin volume over the bones and give it a color, MAYBE some feathers.
But a whale skeleton looks nothing like the mass of flesh of a whale. Skeletons give no clue about an Elephant’s head shape.
So imagine a huge fluffy owl or yellow chick with a trex skeleton deep inside.