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BErMin: A Model Selection Algorithm for Reinforcement Learning Problems
Published on Jan 25, 20124078 Views
We consider the problem of model selection in the batch (offline, non-interactive) reinforcement learning setting when the goal is to find an action-value function with the smallest Bellman error amon
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Chapter list
BErMin: A Model Selection Algorithm for Reinforcement Learning Problems00:00
Given some interaction data - 0100:33
Given some interaction data - 0201:12
How to choose the architecture of the function approximator?01:41
Solution: Adaptive Algorithms02:35
Problem Setup - 0103:45
Problem Setup - 0203:51
Problem Setup - 0305:44
Challenge07:38
What about estimating the effect - 0109:14
What about estimating the effect - 0209:32
Not done yet! - 0111:21
Not done yet! - 0211:33
Algorithm 1 - 0113:44
Algorithm 1 - 0213:52
Assumptions16:19
Theorem16:44
Remember - 0117:19
Remember - 0217:22
Remember - 0317:29
Conclusion18:30