The Origins of Common Sense: Modeling human intelligence with Probabilistic Programs and Program Induction

Speaker Details

Josh Tenenbaum studies learning, reasoning and perception in humans and machines, with the twin goals of understanding human intelligence in computational terms and bringing computers closer to human capacities. His current work focuses on building probabilistic models to explain how people come to be able to learn new concepts from very sparse data, how we learn to learn, and the nature and origins of people’s intuitive theories about the physical and social worlds. He is Professor of Computational Cognitive Science in the Department of Brain and Cognitive Sciences at MIT, and is a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL). He received his Ph.D. from MIT in 1999, and was a member of the Stanford University faculty in Psychology and (by courtesy) Computer Science from 1999 to 2002. His papers have received awards at numerous conferences, including CVPR (the IEEE Computer Vision and Pattern Recognition conference), ICDL (the International Conference on Learning and Development), NIPS, UAI, IJCAI and the Annual Conference of the Cognitive Science Society. He is the recipient of early career awards from the Society for Mathematical Psychology (2005), the Society of Experimental Psychologists, and the American Psychological Association (2008), and the Troland Research Award from the National Academy of Sciences (2011).

Date:
Speakers:
Joshua Tenenbaum
Affiliation:
MIT