From Vice dot com
You can play reconstructions of ancient board games thanks to these scientists and their algorithmsMatthew Gault
August 21, 2019
Cameron Browne doesn’t see games the way you and I do.
“I [deconstruct] them into their mechanisms,” he said. “I have quite a mathematical approach to games.” This perspective comes with the territory when you’re at the forefront of digital archaeoludology, a new field that uses modern computing to understand ancient games, like Browne is.
Humans have played games for millenia, and the oldest known board game is an Egyptian game that dates back to 3100 BCE called Senet. “We almost never have the rules for these early games,” Browne said. “The rules have never been recorded, so our knowledge is largely based on historian’s reconstructions."
Browne is the principal investigator of the Digital Ludeme Project, a research project based at Maastricht University in the Netherlands that’s using computational techniques to recreate the rules of ancient board games. To assist in this work, Browne and his colleagues are working on a general-purpose system for modelling ancient games, as well as generating plausible rulesets and evaluating them. The system is called Ludii, and it implements computational techniques from the world of genetics research and artificial intelligence.
You can check out the Digital Ludeme Project here, and try out a beta version of an app that lets you test out its reconstructions of ancient games such as Hnefatafl—viking chess. While the games are imperfect, the idea is that computers can help scientists narrow down which plausible iterations of ancient games are more fun to play, and thus more likely to have existed in reality.
The first part of the process, Browne said, is to break games down into their constituent parts and codify them in terms of units called “ludemes” in a database. Ludemes can be any existing game pieces or rules that archaeologists know of. Once a game is described in terms of its ludemes, it becomes a bit more like a computer program that machines can understand and analyze for patterns. Cultural information, such as where the game was played, is also recorded to help evaluate the plausibility of new rulesets.
Using techniques from the world of algorithmic procedural generation, the team then uses the information in the database to infer and reconstruct rulesets of varying plausibility and playability for these ancient games.
“This is where the modern AI comes in and helps us evaluate these games from a new perspective,” Browne said. “To possibly help us arrive at more realistic reconstructions of how the games were played."
Next, the team uses algorithms to assess the generated rulesets. Artificially intelligent agents play these ancient games and their variants and build lists of moves. As the AIs play through different rulesets, they generate data about the game’s quality to help researchers determine if a ruleset is viable.
Fun is subjective, but Browne believes there are a few universal yardsticks. Games should have strategic depth, drama (the possibility of a comeback for a losing player), clear victories, a reasonable length, and they shouldn’t end in a draw too often.
The agents that play the games use Monte Carlo tree search, which was implemented in DeepMinds’ AlphaGo AI. However, the Digital Ludeme Project team didn’t want an AI as advanced as AlphaGo and so they didn't implement the deep learning tech that powers AlphaGo. They don’t need AI that can beat the top human players in the world; they just need something that works.
This approach has already found some success. In 2018, archaeologists discovered an ancient Roman board game in a tomb in Slovakia. Piecing together the rules of the game has proved an impossible task for researchers, but Browne and his researchers have a version of the game you can play right now.