Invariant causal prediction for block MDPs
Generalization across environments is critical to the successful application of reinforcement learning (RL) algorithms to real-world challenges. In this work we propose a method for learning state abstractions which generalize to novel observation distributions in the multi-environment RL setting. W...
| Main Authors: | , , , , , , , |
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| 格式: | Conference item |
| 語言: | English |
| 出版: |
Proceedings of Machine Learning Research
2020
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