Satinder Singh (University of Michigan) “Deep Reinforcement Learning for Sequential Decision Making Tasks with Natural Language Interaction”
3400 N Charles St
Baltimore, MD 21218
USA
Abstract
Dr. Satinder Singh is a Professor of Computer Science & Engineering at the University of Michigan where he also served as the Director of the Artificial Intelligence Laboratory from 2006 to 2017. He is also a co-founder and Chief Scientist of Cogitai, Inc. Dr. Singh’s research interests focus on the field of Reinforcement Learning, i.e., on building algorithms, theory, and architectures for software agents that can learn how to act in uncertain, complex, and dynamic environments. Specific interests include building models of dynamical systems from time-series data, learning good interventions in human-machine interaction, dealing with partial observability and hidden state in sequential decision-making, dealing with the challenge of exploration-exploitation and delayed feedback, explaining animal and human decision making using computational models, and optimal querying in semi-autonomous agents based on value of information. He is interested in applications from healthcare, robotics, and game-playing. He is a Fellow of the Association for the Advancement of Artificial Intelligence, was Program Co-Chair of AAAI 2016, has received an outstanding faculty award from his department, and has published over 150 papers in his field.