Turing Award Goes to A.I. Pioneers Andrew Barto and Richard Sutton

In 1977, Andrew Barto, as a researcher at the University of Massachusetts, Amherst, began to explore a new theory that Neurons have behaved like hedonists. The basic idea was that the human brain was driven by billions of nerve cells that each tried to maximize pleasure and minimize pain.

A year later, he was joined by another young researcher, Richard Sutton. Together, they worked to explain human intelligence using this simple concept and applied it to artificial intelligence. The result was “learning to strengthen”, a means for AI systems to learn from the digital equivalent of pleasure and pain.

On Wednesday, the association for computing machinery, the largest global company of IT professionals, announced that Dr. Barto and Dr. Sutton had won this year’s Turing Prize for their work on strengthening. The Turing Prize, which was awarded in 1966, is often called the Nobel Prize in computer science. The two scientists will share the price of $ 1 million with the price.

Over the past decade, learning to strengthen a vital role in the rise of artificial intelligence, including revolutionary technologies such as Google alphago and the Openai Chatppt. The techniques that fed these systems were rooted in the work of Dr. Barto and Dr. Sutton.

“These are the undisputed pioneers of learning to strengthen,” said Oren Etzioni, professor emeritus of computer science at Washington University and founding director of the Allen Institute for Artificial Intelligence. “They generated key ideas – and they wrote the book on the subject.”

Their book, “Reinforcement Learning: An Introduction”, which was published in 1998, remains the final exploration of an idea which, according to many experts, only makes its potential achieve.