creators

Andrew Barto: Turing Award, reinforcement learning

Andrew Barto is professor emeritus at UMass Amherst and co-recipient, with Richard Sutton, of the 2024 ACM A.M. Turing Award for reinforcement learning.

Andrew Gehret Barto, born in 1948, is the American computer scientist who, with his doctoral student Richard Sutton, built the foundations of computational reinforcement learning. He took a BS in mathematics from the University of Michigan in 1970 and a PhD there in 1975 with a thesis on cellular automata as models of natural systems. He arrived at the University of Massachusetts Amherst as a postdoctoral research associate in 1977, became associate professor in 1982 and full professor in 1991, chaired the department from 2007 to 2011, and co-directed the Autonomous Learning Laboratory until retiring in 2012. With Sutton he adapted Markov decision processes to environments whose dynamics and rewards are unknown, which is what made reinforcement learning usable outside theory. Their textbook "Reinforcement Learning: An Introduction" (MIT Press, 1998; second edition 2018) is still the field's standard reference. He received the IEEE Neural Networks Society Pioneer Award in 2004 and the IJCAI Award for Research Excellence in 2017. On 5 March 2025 he and Sutton were named recipients of the 2024 ACM A.M. Turing Award, and UMass Amherst gave him a Distinguished Achievement Award at its May 2026 commencement. He is professor emeritus in the Manning College of Information and Computer Sciences.

Specialization

reinforcement learning, machine learning theory, computational neuroscience

Country

United States