VariBAD: a very good method for Bayes-adaptive deep RL via meta-learning
Trading off exploration and exploitation in an unknown environment is key to maximising expected return during learning. A Bayes-optimal policy, which does so optimally, conditions its actions not only on the environment state but on the agent’s uncertainty about the environment. Computing a Bayes-o...
| 主要な著者: | , , , , , , |
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| フォーマット: | Conference item |
| 言語: | English |
| 出版事項: |
International Conference on Learning Representations
2020
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