Out of the Box

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사이트 도구

추적: • ssh
drl:start

차이

문서의 선택한 두 판 사이의 차이를 보여줍니다.

차이 보기로 링크

양쪽 이전 판이전 판
다음 판		이전 판
drl:start [2017/04/27 04:06] – [General Video Game Playing 관련연구 목록] rex8312drl:start [2024/03/23 02:42] (현재) – 바깥 편집 127.0.0.1
줄 4: 줄 4:
  
   * [[https://arxiv.org/abs/1704.04651|The Reactor: A Sample-Efficient Actor-Critic Architecture]]   * [[https://arxiv.org/abs/1704.04651|The Reactor: A Sample-Efficient Actor-Critic Architecture]]
 +
 +==== Reward Shaping ====
 +
 +  * [[https://arxiv.org/abs/1611.05397|Reinforcement Learning with Unsupervised Auxiliary Tasks]]
 +
 ==== Simulation ==== ==== Simulation ====
  
줄 31: 줄 36:
   * Progressive Network   * Progressive Network
     * A. A. Rusu et al., “Progressive neural networks,” arXiv preprint arXiv:1606.04671, 2016.     * A. A. Rusu et al., “Progressive neural networks,” arXiv preprint arXiv:1606.04671, 2016.
 +  * [[https://arxiv.org/pdf/1310.8499.pdf|2014-05, Deep AutoRegressive Networks]]
  
  
줄 54: 줄 60:
 ^Dueling Network | Z. Wang, N. de Freitas, and M. Lanctot, “Dueling network architectures for deep reinforcement learning,” arXiv preprint arXiv:1511.06581, 2015.| ^Dueling Network | Z. Wang, N. de Freitas, and M. Lanctot, “Dueling network architectures for deep reinforcement learning,” arXiv preprint arXiv:1511.06581, 2015.|
  
-==== Memory ==== 
  
-^Neural Turing Machine  |A. Graves, G. Wayne, and I. Danihelka, “Neural Turing Machines,” arXiv:1410.5401 [cs], Oct. 2014.| 
-^External Memory |A. Graves et al., “Hybrid computing using a neural network with dynamic external memory,” Nature, vol. 538, no. 7626, pp. 471–476, Oct. 2016. | 
  
-==== Reward Shaping ==== 
  
-^[[DRDL:UNREAL]] |[1]M. Jaderberg et al., “Reinforcement Learning with Unsupervised Auxiliary Tasks,” arXiv:1611.05397 [cs], Nov. 2016. |  
 ==== AI Platform ==== ==== AI Platform ====
  
줄 75: 줄 76:
 ^Anold |G. Lample and D. S. Chaplot, “Playing FPS Games with Deep Reinforcement Learning,” arXiv:1609.05521 [cs], Sep. 2016. | ^Anold |G. Lample and D. S. Chaplot, “Playing FPS Games with Deep Reinforcement Learning,” arXiv:1609.05521 [cs], Sep. 2016. |
  
 +===== 구현체 =====
  
-{{tag>DRL deep-learning reinforcement-learning}}+  * https://github.com/google/dopamine
      
  
  
  
drl/start.1493265974.txt.gz · 마지막으로 수정됨: (바깥 편집)