Q-Learning: Model Free Reinforcement Learning and Temporal Difference Learning - presented by Prof. Steven L. Brunton

Q-Learning: Model Free Reinforcement Learning and Temporal Difference Learning

Prof. Steven L. Brunton

Prof. Steven L. Brunton
Q-Learning: Model Free Reinforcement Learning and Temporal Difference Learning
Prof. Steven L. Brunton
Steven L. Brunton
University of Washington

Here we describe Q-learning, which is one of the most popular methods in reinforcement learning. Q-learning is a type of temporal difference learning. We discuss other TD algorithms, such as SARSA, and connections to biological learning through dopamine. Q-learning is also one of the most common frameworks for deep reinforcement learning.

References
  • 1.
    https://openlibrary.org/isbn/9781108422093
Brunton Lab logo
Reinforcement learning
Brunton Lab (University of Washington)
Cite as
S. L. Brunton (2022, January 14), Q-Learning: Model Free Reinforcement Learning and Temporal Difference Learning
Share
Details
Listed seminar This seminar is open to all
Recorded Available to all
Video length 35:34