Learning retrospective knowledge with reverse reinforcement learning
We present a Reverse Reinforcement Learning (Reverse RL) approach for representing retrospective knowledge. General Value Functions (GVFs) have enjoyed great success in representing predictive knowledge, i.e., answering questions about possible future outcomes such as “how much fuel will be consumed...
| Main Authors: | , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
NeurIPS
2020
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