Foundations of Autonomous Decision Making under Uncertainty
10-734, Fall 2025
Aarti Singh
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Lecture: |
Date and Time: Tuesday and Thursday, 9:30 - 10:50 am Location: GHC 4211 |
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Course Description: |
AI is increasingly being used not only for prediction but for decision making in the real-world. Algorithms for autonomous decision making need to rely on the uncertainty of predictions, in addition to accuracy, to identify potentially good decisions that may not have been tried. This course will cover foundations of AI algorithms used for making decisions in the face of uncertainty starting from stochastic experimental design and Gaussian process optimization to advanced methods for sequential decisions such as bandits, online learning, active learning, and reinforcement learning. We will discuss these methods, analysis techniques, their sample and computational complexities, as well as open challenges related to these methods. Outline of lecture schedule is available here and a detailed syllabus is available on Canvas. |
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| Prerequisites: |
10-701 or 10-715, 10-716
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