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Skip to Search Results- 2representation learning
- 1geometric task structures
- 1learning by watching
- 1online learning
- 1reinforcement learning
- 1robotic task specification
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Spring 2022
The concept of state is fundamental to a reinforcement learning agent. The state is the input to the agent's action-selection policy, value functions, and environmental model. A reinforcement learning agent interacts with the environment by performing actions and receiving observations, resulting...
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Fall 2021
This thesis studies how to enable a real-world robot to efficiently learn a new task by watching human demonstration videos. We propose to introduce a geometric task structure as an interpretable inductive bias to the learning problem. We aim to learn a representation that geometrically encodes...