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Reinforcement Learning Theory

Reinforcement Learning Theory

This video was recorded at Machine Learning Summer School (MLSS), Taipei 2006. The tutorial is on several new pieces of Reinforcement learning theory developed in the last 7 years. This includes: 1. Sample based analysis of RL including E3 and sparse sampling. 2. Generalization based analysis of RL including conservative policy iteration and RL-to-Classification reductions. For each of these forms of theory, we cover the basic results and cover the weaknesses and strengths of the approach in context.
Keywords:
videolectures, ocwc, oec
Disciplines:
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More about this material

Material Type:
Open (Access) Textbook
Date Added to MERLOT:
February 10, 2015
Date Modified in MERLOT:
February 10, 2015
Author:
Submitter:
The Open Education Consortium
Primary Audience:
College General Ed, College Lower Division, College Upper Division
Technical Format:
Video
Mobile Compatibility:
Not specified at this time
Language:
English
Cost Involved:
No
Source Code Available:
No
Creative Commons:
Creative Commons License
This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States

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