Biography

Andrew Barto is Professor Emeritus of Computer Science, University of Massachusetts, Amherst, having retired in 2012. He served as Chair of the UMass Department of Computer Science from 2007 to 2011.  He received his B.S. with distinction in mathematics from the University of Michigan in 1970, and his Ph.D. in Computer Science in 1975, also from the University of Michigan. He joined the Computer Science Department of the University of Massachusetts Amherst in 1977 as a Postdoctoral Research Associate, became an Associate Professor in 1982, and has been a Full Professor since 1991. He is Co-Director of the Autonomous Learning Laboratory and an Associate Member of the Neuroscience and Behavior Program of the University of Massachusetts.  He currently serves as an associate editor of Neural Computation, as a member of the Advisory Board of the Journal of Machine Learning Research, as a member of the editorial boards of Adaptive Behavior and Frontiers in Decision Neuroscience. Professor Barto is a Fellow of the American Association for the Advancement of Science, a Life Fellow of the IEEE, and a member of the Society for Neuroscience. He received the 2004 IEEE Neural Network Society Pioneer Award for contributions to the field of reinforcement learning, and the IJCAI-17 Award for Research Excellence for groundbreaking and impactful research in both the theory and application of reinforcement learning. He has published over one hundred papers or chapters in journals, books, and conference and workshop proceedings. He is co-author with Richard Sutton of the book “Reinforcement Learning: An Introduction,” MIT Press 1998, which has received over 24,000 citations.

Abstract

The Learning Machines of John Andreae

John Andreae developed a series of learning systems beginning in the early 1960s. In 1992 he retired from a professorship in the Electrical Engineering Department, University of Canterbury, Christchurch, New Zealand, but continues, at 90 years of age, to pursue his research toward a conscious robot. In this talk I will discuss ideas he incorporated into his learning systems, with particular attention to those that foreshowed some that we are thinking about today.