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Model-based reinforcement learning (RL) algorithms designed for handling complex visual observations typically learn some sort of latent state representation, either explicitly or implicitly.
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Contrastive variational model-based reinforcement learning for complex observations
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Which mutual-information representation learning objectives are sufficient for control?
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