Making reinforcement learning more data-efficient
Recently, researchers showed that applying deep neural networks to Reinforcement Learning (RL) can improve the agent’s ability to learn action policies directly from high dimensional input states. However, there are still several challenges present when applying these algorithms to real world...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/149413 |