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1
Intro
2
Classical Reinforcement Learning
3
Motivation
4
Meaning of robustness
5
Three Types of Uncertainties
6
Applicability
7
Introduction - Planning with Parameter Uncertainty
8
Background: Robust MDPS
9
Robust Policy Evaluation
10
Part 2
11
Action Robustness
12
Some results
13
Posterior Uncertainty Sets: Online Construction of Uncertainty Sets
14
Uncertainty Robust Bellman Equation
15
Deep Learning Approximation
16
Conclusion
Description:
Explore deep robust reinforcement learning and regularization in this 31-minute lecture by Shie Mannor from Technion. Delve into classical reinforcement learning concepts before examining the meaning of robustness and three types of uncertainties. Investigate planning with parameter uncertainty, robust MDPs, and robust policy evaluation. Learn about action robustness, posterior uncertainty sets, and the uncertainty robust Bellman equation. Conclude with insights on deep learning approximation in the context of robust reinforcement learning.

Deep Robust Reinforcement Learning and Regularization

Simons Institute
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