A survey of reinforcement learning informed by natural language
To be successful in real-world tasks, Reinforcement Learning (RL) needs to exploit the compositional, relational, and hierarchical structure of the world, and learn to transfer it to the task at hand. Recent advances in representation learning for language make it possible to build models that acqui...
| Main Authors: | , , , , , , , |
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| 格式: | Conference item |
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International Joint Conferences on Artificial Intelligence
2019
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