Improving Generalization in Reinforcement Learning using Policy Similarity Embeddings

Posted by Rishabh Agarwal, Research Associate, Google Research, Brain Team Reinforcement learning (RL) is a sequential decision-making paradigm for training intelligent agents to tackle complex tasks such as robotic locomotion, playing video games, flying stratospheric balloons and designing hardware chips. While RL agents have shown promising results in a variety of activities, it is difficult to transfer the capabilities of these agents to new tasks, even when these tasks are semantically equi...

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