Technology built to create content for video games can be used to teach robots to solve new tasks, writes Sebastian Risi, Professor at the Danish IT University (ITU) in an article published on Monday in the acclaimed scientific journal Nature Machine Learning.
Risi wrote the article in collaboration with former ITU researcher Julian Togelius, who is currently an Associate Professor at the New York University. According to the authors, the Procedural Content Generation (PCG) can make it easier to train robots' ability to solve a given task in a computer simulation.
”We hope that PCG will become more mainstream in within artificial intelligence. It can both save a lot of money, and in the long run, it can help to create robots that can solve several different and more complex tasks,” Risi said.
Gaming technology and Artificial Intelligence
The gaming industry has long made use of PCG, a technology that makes it possible to create games that change every time you play, for example in the form of levels, maps, characters and so forth.
The use of PCG has already been integrated with the field of artificial intelligence, where programmers have created content for games that is now being used as training data for robots.
More Cost Efficient
Training data is crucial in the development of robot technology. Before a robot will be able to solve a task, it must first learn the task through a computer simulation. However, if the reality deviates a fraction from the data used in the simulation, the robot will have to re-learn the task all over again, and such task-training often turns out to be rather costly.
Risi believes that this problem can be solved much more efficiently with the use of PCG, as the computer can continuously generate more training data.
”By letting the computer generate training sets, we can speed up development and reduce costs. In the long run, PCG can be an important step towards creating more robust and general artificial intelligence. Evolution has taught us humans to handle new tasks constantly, so we are good at adapting. We want to give the robots that ability so that they can solve tasks they have not been given before,” Risi commented
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