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The sport of curling is well known in Scotland, where records of it date back to the early 16th century.
Indeed, when an old pond in Dunblane was drained, two ancient curling stones were uncovered, one dated 1511, the other 1551. In those days the game, somewhat similar to bowling on ice, consisted of two competing teams sliding flat rocks on frozen rivers or ponds aiming at a target. So in a suitably icy winter, the game was accessible to all and became a popular competitive sport. From its beginnings in Scotland, curling took hold in northern Europe, and then followed the Scottish diaspora as far afield as Canada and New Zealand.
Today curling has evolved from a casual outdoor village game to a fiercely competitive international team sport that became a medal sport in the winter Olympic games in 1998. Now curling matches are conducted indoors on a curling sheet covered with pebbled ice. But despite this standardisation, the game includes many variables that alter the properties of the ice surface, such as temperature, humidity and previous stone trajectories, each of which changes as the game proceeds. Players employ sophisticated strategies to outwit their opponents while causing the stone to follow a curved path or curl – hence the name of the game. Also, two sweepers with brooms are employed to reduce ice friction ahead of a moving stone so influencing its path.
Clearly curling has many inbuilt uncertainties, and this has attracted the attention of artificial intelligence (AI) scientists to use the game ‘as a testbed for demonstrating the interaction between an AI system and a highly non stationary real-world scenario.’*
Robots have already beaten top professionals at games like chess and poker, but could they master the much more unpredictable game of curling with its dynamically changing environment?
To take on the challenge scientists built a robot which they named Curly, which can perform adaptive actions in response to the continuous environmental change exemplified by curling.
And yes, Curly won three of four official matches against expert human teams. I don’t, however, expect to see him in an Olympic team any time soon!
* Won et al, Sci Robot 5, eabb9764 (2020).