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Found 2 papers, 1 papers with code
Visual Transfer for Reinforcement Learning via Wasserstein Domain Confusion
We introduce Wasserstein Adversarial Proximal Policy Optimization (WAPPO), a novel algorithm for visual transfer in Reinforcement Learning that explicitly learns to align the distributions of extracted features between a source and target task.
Zero-Shot Policy Transfer with Disentangled Attention
In such settings, agents are trained in similar environments, such as simulators, and are then transferred to the original environment.
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