Above: the possible gameboard with pencil marks highlighting the incised lines. Below: diagram of the lines, indicating how pieces may have been moved along them to play the game
Image Credit: Walter Crist
Scientific Frontline: "At a Glance" Summary: AI Decoding of an Ancient Roman Board Game
- Main Discovery: Researchers successfully utilized artificial intelligence to decode the rules of an ancient, previously unexplainable board game carved into a limestone object discovered in the Roman Netherlands.
- Methodology: The research team employed the AI-driven play system Ludii to simulate hundreds of rule sets from documented ancient European games, systematically adjusting parameters to identify which simulated movements replicated the specific, asymmetrical wear patterns observed on the original artifact.
- Key Data: The AI simulations consistently reproduced the concentrated friction and uneven wear along the carved lines when applying rules for a "blocking game," characterized by asymmetrical play where a player with more pieces attempts to trap an opponent with fewer pieces.
- Significance: This study represents the first successful integration of AI-driven simulated play with archaeological analysis to identify a board game, providing physical evidence that blocking games existed long before their earliest prior documentation in the Middle Ages.
- Future Application: This computational approach establishes a new analytical framework for archaeologists to interpret mysterious historical artifacts and reconstruct undocumented cultural practices when written texts or artworks have not survived.
- Branch of Science: Archaeology, Computer Science, and Cultural History.
- Additional Detail: The artifact provided a rare preservation opportunity, as most everyday Roman games were historically drawn in dust or carved into perishable materials like wood, leaving minimal physical evidence for modern physical analysis.
 |
| Results of the AI-driven simulation that produced asymmetrical play along the relevant diagonal line. These are games in which the player with more pieces attempts to block the player with fewer pieces. Pieces are illustrated in their starting positions; where no pieces begin on the board they are placed alternately until all are placed. White indicates player one. Boards are shown after transformation with the most-used diagonal on the bottom right Image Credit: figure by authors |
For the first time, an international research team has harnessed artificial intelligence (AI) to decode the rules of an ancient board game, pioneering a new way to reveal long-lost historical secrets.
By analyzing 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 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 restoration studio Restaura in Heerlen.
The object, found in what is now Heerlen in the Netherlands, features a pattern of unusual intersecting lines that had 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 specializes in ancient games.
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.
Using the AI-driven play system Ludii, the researchers made two AI agents play against each other using the object as a board, utilizing 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.
“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.
“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.”
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 modeling, 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.”
Acknowledgements: Computing resources were provided by the Dutch national e-infrastructure with the support of the SURF co-operative (EINF-3845 ‘Analysing Traditional Game Properties and Concepts’; EINF-4028 ‘Evaluation of Trained AIs for General Game Playing’), of the research program Computing Time on National Computer Facilities (partly financed by the Nederlandse Organisatie voor Wetenschappelijk Onderzoek). Further discussion of results and applications were made possible through European Cooperation in Science and Technology (COST) Action #CA22145 ‘Computational Techniques for Tabletop Games Heritage (GameTable)’. Open access funding provided by Leiden University.
Funding: This research was funded by the European Research Council as part of Consolidator Grant #771292 ‘Digital Ludeme Project’.
Published in journal: Antiquity
Authors: Walter Crist, Éric Piette, Karen Jeneson , Dennis J.N.J. Soemers, Matthew Stephenson, Luk van Goor, and Cameron Browne
Source/Credit: Flinders University
Reference Number: arch032126_01