Richard S. Sutton
| Richard S. Sutton | |
|---|---|
| Residence | Canada |
| Fields |
Artificial Intelligence Reinforcement Learning |
| Institutions | University of Alberta |
| Alma mater |
University of Massachusetts at Amherst Stanford University |
| Thesis | Temporal credit assignment in reinforcement learning (1984) |
| Doctoral advisor | Andrew Barto |
| Doctoral students |
Doina Precup David Silver Hamid Maei Adam White |
| Known for | Temporal difference learning, Dyna, Options, GQ(λ) |
| Notable awards |
AAAI Fellow (2001) President's Award (INNS) (2003) Royal Society of Canada Fellow (2016) |
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Website incompleteideas |
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Richard S. Sutton is a Canadian computer scientist. Currently he is professor of Computer Science and iCORE chair at the University of Alberta. Dr. Sutton is considered one of the founding fathers of modern computational reinforcement learning, having several significant contributions to the field, including temporal difference learning, policy gradient methods, the Dyna architecture.
Sutton received his B.A. degree at the Stanford University in Psychology in 1978, M.Sc. and Ph.D in computer science from University of Massachusetts at Amherst in 1980 and 1984, respectively, under the supervision of Andrew Barto. His doctoral dissertation was entitled "Temporal Credit Assignment in Reinforcement Learning", where he introduced actor-critic architectures and "temporal credit assignment".
In 1984 Dr. Sutton held a postdoctoral position at University of Massachusetts at Amherst. From 1985 to 1994 he was a Principal Member of Technical Staff in the Computer and Intelligent Systems Laboratory at GTE Laboratories. In 1995 he returned to University of Massachusetts at Amherst as a Senior Research Scientist, position he held until 1998, when he joined the AT&T Shannon Laboratory as Principal Technical Staff Member in the Artificial Intelligence Department. Since 2003 he is Professor and iCORE Chair in the Department of Computing Science at the University of Alberta, where he leads the Reinforcement Learning and Artificial Intelligence Laboratory (RLAI).
Sutton, R. S., Barto, A. G., Reinforcement Learning: An Introduction. MIT Press, 1998. Also translated into Japanese and Russian. Second edition in progress.
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