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Constrained Deep Q-Learning Gradually Approaching Ordinary Q-Learning
A deep Q network (DQN) (Mnih et al., 2013) is an extension of Q learning, which is a typical deep reinforcement learning method. In DQN, a Q function expresses all action values under all states, and it is approximated using a convolutional neural network. Using the approximated Q function, an optim...
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| Yayımlandı: | Front Neurorobot |
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| Asıl Yazarlar: | , , , , , |
| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
Frontiers Media S.A.
2019
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| Konular: | |
| Online Erişim: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6914867/ https://ncbi.nlm.nih.gov/pubmed/31920613 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnbot.2019.00103 |
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