Difference between revisions of "10-601 Markov Decision Processes and Reinforcement Learning"
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| − | * [http://curtis.ml.cmu.edu/w/courses/images/ | + | * [http://curtis.ml.cmu.edu/w/courses/images/1/1b/Lecture24-RL.pdf Slides in PDF] |
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=== Readings === | === Readings === | ||
Latest revision as of 10:24, 1 December 2013
Slides
Readings
Taking home message
- What distinguishes RL from Supervised Learning and Unsupervised Learning?
- Elements of a Markov Decision Process
- Both value iteration and policy iteration are standard algorithms for solving MDPs, and there isn't currently universal agreement over which algorithm is better.
- Q-learning is model-free, and explore the temporal difference
