Looks like computer scientists working in the field of artificial intelligence have got some help from football players.
By watching the Oregon State University Beavers play football, scientists have made an important advance that blends computer vision, machine learning and automated planning, and created a new system that may improve everything from factory efficiency to airport operation or nursing care.
The idea is for a computer to observe a complex operation, learn how to do it, and then optimize those operations or accomplish other related tasks.
In this project, the goal is for the computer to watch video of football plays, learn from them, and then design plays and control players in a football simulation or video game.
As it turns out, football is very complex, and computers struggle to see and understand plays a coach or even an average fan would find routine.
“This is one of the first attempts to put several systems together and let a computer see something in the visual world, study it and then learn how to control it,” said Alan Fern, an associate professor of computer science at OSU.
“Football actually makes a pretty good test bed, because it’s much more complicated that you might think both visually and strategically, but also takes place in a structured setting,” he said.
“This makes it quite analogous to other potential applications,” he added.
“Using football, we created learning algorithms that allow the computer to see the plays, analyze them and learn from them,” said Fern.
“Ultimately these systems should be able to see what is happening, understand it and maybe even improve upon it,” he added.
The work could have multiple applications. Control and logistics planning is hugely important in industry, and even small improvements in efficiency could save billions of dollars. Computer vision and controls might be useful in hospitals or nursing homes to help monitor patients and see who needs care. Large operations such as an airport offer multiple control challenges, or the military could use such approaches to improve supply chains for troops in the field.
The study has been published in AI Magazine.