EEC 256
— Reinforcement Learning
Reinforcement Learning (RL) is the subset of machine learning, the core of artificial intelligence. Topics include fundamentals of RL, bandit problems, Markov decision processes, and dynamic programming.
Topics
- fundamentals of RL
- bandit problems
- Markov decision processes
- and dynamic programming
Topics explicitly listed in official catalogue description
Prerequisites & course information
Course Description: Reinforcement Learning (RL) is the subset of machine learning, the core of artificial intelligence. Topics include fundamentals of RL, bandit problems, Markov decision processes, and dynamic programming. Learning Activities: Lecture 4 hour(s). Grade Mode: Letter. Learning Activities: Lecture 4 hour(s). Grade Mode: Letter.
Sources
- Course catalogue ↗2026-2027