Reinforcement Learning Theory

author: John Langford, Microsoft Research
published: Feb. 25, 2007,   recorded: July 2006,   views: 2255
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Description

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.

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Download slides icon Download slides: mlss06tw_langford_rlt.pdf (204.9┬áKB)


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