AI Decodes Ancient Roman Board Game And Reveals Lost Rules From 2,000 Years Ago

By analysing an engraved limestone object from the Roman Netherlands, the team was able to determine likely game rules, based on its distinctive markings

The new research, published in the Antiquity journal, was led by Maastricht University (The Netherlands) and Leiden University (The Netherlands), with input from Flinders University (South Australia), the Université Catholique de Louvain (Belgium), and the Roman Museum and the restoration studio Restaura in Heerlen.

Archaeological Mystery of the Heerlen Gam,tone

The object, found in what is now Heerlen in the Netherlands, features a pattern of unusual intersecting lines that has puzzled archaeologists for decades.

Because most everyday Roman games were drawn in dust or carved into wood (materials unlikely to survive), this carefully shaped limestone piece offered a rare opportunity to investigate ancient gameplay.

"The stone shows a geometric pattern and visible wear that are consistent with sliding game pieces across the surface, which point strongly to repeated play rather than another purpose," says lead author, Dr Walter Crist, an archaeologist at Leiden University who specialises in ancient games.

AI Simulations to Reconstruct Game Rules

To determine whether the stone was a game board and how it worked, the research team used AI to simulate hundreds of possible rule sets, to see which produced the same patterns of wear found on the object.

"The uneven wear along the carved lines raises a key question about whether AI-driven simulated play could reproduce that same pattern," says Dr Crist.

Ludii System and Comparative Game Models

Using the AI-driven play system Ludii, the researchers made two AI agents play against each other using the object as a board, utilising rule sets from many ancient board games documented in Europe, such as haretavl from Scandinavia and gioco dell'orso from Italy.

Flinders University computer scientist, Dr Matthew Stephenson, says that using modern AI techniques can bridge the gap between historical and computational studies of games.

"We ran the simulations repeatedly, adjusting rules each time to see which movements would cause the same concentrated friction seen on the original stone," says Dr Stephenson, from Flinders' College of Science and Engineering.

Blocking Game Strategy Identified by AI

"The simulations pointed strongly to a type of strategy game known as a blocking game. In blocking games, players try to trap their opponent's pieces by preventing movement rather than capturing them."

Because blocking games are scarcely documented before the Middle Ages, the findings suggest such games may have a deeper history than previously documented, whilst the study also demonstrates the transformative potential of AI for archaeology.

AI as a Tool for Archaeological Discovery

"This is the first time that AI-driven simulated play has been used together with archaeological methods to identify a board game," says Dr Crist.

"It offers archaeologists a promising new tool for understanding ancient games that don't resemble those known from surviving texts or artworks."

Digital Ludeme Project and Future Applications

This work took place at Maastricht University and as part of the Digital Ludeme Project in Europe, which used artificial intelligence to produce more reliable reconstructions of ancient games that are plausible both historically and mathematically.

By blending archaeology, digital modelling, and cultural history, the team provided a clearer understanding of an object that once seemed unexplainable.

"The success of this approach suggests that many other mysterious artefacts may hold hidden stories waiting to be uncovered with the help of modern technology," says Dr Stephenson.

"It shows how AI can contribute to our understanding of materials that would otherwise be difficult to interpret."