Month: April 2018

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Evolved Policy Gradients

We’re releasing an experimental metalearning approach called Evolved Policy Gradients, a method that evolves the loss function of learning agents, which can enable fast training on...

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Retro Contest

We’re launching a transfer learning contest that measures a reinforcement learning algorithm’s ability to generalize from previous experience.

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