Policy Gradient Methods

Mirror Descent Policy Optimization

Introduced by Tomar et al. in Mirror Descent Policy Optimization

Mirror Descent Policy Optimization (MDPO) is a policy gradient algorithm based on the idea of iteratively solving a trust-region problem that minimizes a sum of two terms: a linearization of the standard RL objective function and a proximity term that restricts two consecutive updates to be close to each other. It is based on Mirror Descent, which is a general trust region method that attempts to keep consecutive iterates close to each other.

Source: Mirror Descent Policy Optimization

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Continuous Control 1 100.00%

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🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

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