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Register a new userEfficient iterative policy optimization
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Added by
Nicolas Le Roux
Publication date
2016
fields
Informatics Engineering
and research's language is
English
Authors
Nicolas Le Roux
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We tackle the issue of finding a good policy when the number of policy updates is limited. This is done by approximating the expected policy reward as a sequence of concave lower bounds which can be efficiently maximized, drastically reducing the number of policy updates required to achieve good performance. We also extend existing methods to negative rewards, enabling the use of control variates.
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