In 1977, Andrew Barto, as a researcher at the University of Massachusetts, Amherst, began exploring a new theory that neurons behaved like hedonists. The basic idea was that the human brain was driven by billions of nerve cells that were each trying 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 “reinforcement learning,” a way for A.I. systems to learn from the digital equivalent of pleasure and pain. On Wednesday, the Association for Computing Machinery, the world’s largest society of computing professionals, announced that Dr. Barto and Dr. Sutton had won this year’s Turing Award for their work on reinforcement learning. The Turing Award, which was introduced in 1966, is often called the Nobel Prize of computing. The two scientists will share the $1 million prize that comes with the award.

Full story : Reinforcement learning pioneers Andrew Barto and Richard Sutton win the 2024 Turing Award; their work contributed to the rise of AI, like AlphaGo and ChatGPT.