Andrew G. Barto and Richard S. Sutton have been named as the recipients of the 2024 ACM A.M. Turing Award for their contributions to the field of reinforcement learning beginning in the 1980s.
Reinforcement learning is a training method for AI systems that teaches them how to make the most optimal decisions through a series of signals known as rewards. ChatGPT, for instance, was trained using a method called reinforcement learning from human feedback (RLHF).
They wrote the textbook “Reinforcement Learning: An Introduction” in 1998, and it is still a standard reference in the field, having been cited over 75,000 times.
Barto and Sutton were responsible for developing many of the basic algorithmic approaches used in reinforcement learning, including temporal difference learning, policy-gradient methods, and using neural networks to represent learned functions.
Their work has also led to discoveries in the neuroscience field, specifically that certain reinforcement learning algorithms can explain the dopamine system in the brain.
“Barto and Sutton’s work demonstrates the immense potential of applying a multidisciplinary approach to longstanding challenges in our field,” said Yannis Ioannidis, president of ACM. “Research areas ranging from cognitive science and psychology to neuroscience inspired the development of reinforcement learning, which has laid the foundations for some of the most important advances in AI and has given us greater insight into how the brain works. Barto and Sutton’s work is not a stepping stone that we have now moved on from. Reinforcement learning continues to grow and offers great potential for further advances in computing and many other disciplines. It is fitting that we are honoring them with the most prestigious award in our field.”
Barto is Professor Emeritus of Information and Computer Sciences at the University of Massachusetts Amherst, and Sutton is a Professor of Computer Science at the University of Alberta, a Research Scientist at Keen Technologies, and a Fellow at Alberta Machine Intelligence Institute.