Learn what matters: cross-domain imitation learning with task-relevant embeddings
We study how an autonomous agent learns to perform a task from demonstrations in a different domain, such as a different environment or different agent. Such cross-domain imitation learning is required to, for example, train an artificial agent from demonstrations of a human expert. We propose a sca...
| Main Authors: | , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
Curran Associates
2023
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