Deep reinforcement learning with robust deep deterministic policy gradient
Recently, Deep Deterministic Policy Gradient (DDPG) is a popular deep reinforcement learning algorithms applied to continuous control problems like autonomous driving and robotics. Although DDPG can produce very good results, it has its drawbacks. DDPG can become unstable and heavily dependent on se...
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主要な著者: | Teckchai Tiong, Ismail Saad, Kenneth Tze Kin Teo, Herwansyah Lago |
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フォーマット: | Proceedings |
言語: | English |
出版事項: |
IEEE Xplore
2020
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主題: | |
オンライン・アクセス: | https://eprints.ums.edu.my/id/eprint/27893/1/Deep%20reinforcement%20learning%20with%20robust%20deep%20deterministic%20policy%20gradient-Abstract.pdf https://eprints.ums.edu.my/id/eprint/27893/ https://ieeexplore.ieee.org/document/9309539 |
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