ACM has named Andrew G. Barto and Richard S. Sutton as the recipients of the 2024 ACM A.M. Turing Award for developing the conceptual and algorithmic foundations of reinforcement learning.
In a series of papers beginning in the 1980s, Barto and Sutton introduced the main ideas, constructed the mathematical foundations, and developed important algorithms for reinforcement learning—one of the most important approaches for creating intelligent systems.
Their work laid the groundwork for the practical application of reinforcement learning in its merging with deep learning.
Barto is Professor Emeritus of information and computer sciences at the University of Massachusetts, Amherst. 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.
Although Barto and Sutton’s algorithms were developed decades ago, major advances in the practical applications of RL came about in the past fifteen years by merging RL with deep learning algorithms
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