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MS&E 338

Reinforcement Learning: Frontiers

  • Not Offered

3 units

Letter or Credit/No Credit

This class covers subjects of contemporary research contributing to the design of reinforcement learning agents that can operate effectively across a broad range of environments. Topics include exploration, generalization, credit assignment, and state and temporal abstraction. An important component of the class is a research project aimed at understanding a focused issue in reinforcement learning. Can be repeated for credit. Prerequisites: 226, CS 234, or EE 277, and experience with mathematical proofs.

Course Prequisites

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