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Found 3 papers, 3 papers with code
Multi-view Disentanglement for Reinforcement Learning with Multiple Cameras
To overcome these hardware constraints, we propose Multi-View Disentanglement (MVD), which uses multiple cameras to learn a policy that achieves zero-shot generalisation to any single camera from the training set.
Deep Reinforcement Learning for Multi-Agent Interaction
The development of autonomous agents which can interact with other agents to accomplish a given task is a core area of research in artificial intelligence and machine learning.
Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning
Reinforcement Learning (RL) agents are often unable to generalise well to environment variations in the state space that were not observed during training.
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