EECE5614 (Reinforcement Learning and Decision Making Under Uncertainty) course reviews and ratings at Northeastern (NEU). Compare professors with RateMyProfessor reviews.
Covers fundamentals of reinforcement learning. Begins with multiarmed bandit problems and basics of exploration and exploitation. Relates the key concepts of decision theory to dynamic programming and reinforcement learning. Discusses well-known off-policy and on-policy temporal difference learning methods. Connects reinforcement learning to key concepts in reasoning under uncertainty. Covers large-scale learning methods, including deep-value-based and policy-based methods. Explores reinforcement learning applications in robot navigation in uncertain and complex environments. Describes the applications of reinforcement learning in genomics and systems biology, including the derivation of intervention strategies for treating chronic diseases such as cancer.
Data updated October 2026.