Computer science professor emeritus Andrew Barto was selected as the 2014 recipient of the International Neural Network Society’s (INNS) Hebb Award “in recognition of long-standing contribution and achievements in biological and computational learning.”
According to INNS awards committee, the Hebb award is “presented annually to senior, highly accomplished researchers for outstanding contributions made in the field of neural networks.” It is named after psychologist Donald O. Hebb, a pioneer in neuropsychology. The award will be presented by the INNS president at the 2014 International Joint Conference on Neural Networks in Beijing in July.
Barto’s primary research contributions are in the field of machine learning, in particular in reinforcement learning, a framework inspired from its study in biology and psychology. Barto continues to co-direct the Autonomous Learning Laboratory, formerly known as the Adaptive Networks Laboratory. His current research centers on what psychologists call intrinsically motivated behavior, meaning behavior that is done for its own sake rather than as a step toward solving a specific problem. He has authored more than 100 publications. He is co-author with Richard Sutton of the book “Reinforcement Learning: An Introduction,” (MIT Press 1998) that has been cited more than 15,000 times.
Barto, who retired in 2012, received the 2004 IEEE Neural Network Society Pioneer Award for his contributions to the field of reinforcement learning. He is a fellow of the American Association for the Advancement of Science, a fellow and senior member of the IEEE, and a member of the American Association for Artificial Intelligence and the Society for Neuroscience.