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For online training, we may have to ditch the complexities of PPO and use a more basic form of temporal difference learning that does not rely on advantage estimation.
We also need to decide which …
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This issue proposes a pyro.contrib.agents module for building agent-based models and using control to guide their actions to maximize rewards.
This modeling task is commonly described as model-bas…
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- 논문에서 얻은 인사이트 정리
- 코드로 구현하는 방법 정리
- 우리꺼에 어떻게 적용할 수 있을지..? 생각하기
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Appetizer for 3D, Neural rendering with GAN, GIRAFFE, CVPR2021 best paper
- https://a…
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Is the process stopping because I requested only 2 ideas to be generated?
I'm also curious about how to obtain the full paper.
I've been waiting for an hour, and the GPT API usage has been stu…
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### Description
### **Concept introduction**
The fact that SPMD has no scheduling overhead gives it the best performance, but it is often not easy enough to develop complex training tasks. For exa…
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Hi!
Let's bring the reinforcement learning course to all the Russian-speaking community 🌏
Would you want to translate? Please follow the 🤗 [TRANSLATING guide](https://github.com/huggingface/tran…
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Presneter: Teawon Kim
Slide: [20171023_neuroevolution.pdf](https://oss.navercorp.com/ClovaVision/PaperReview/files/36449/20171023_neuroevolution.pdf)
Title: From Genetic algorithm to Neuro-Evolu…
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https://arxiv.org/abs/1805.12114
- Kurtland Chua, Roberto Calandra, Rowan McAllister, Sergey Levine
- Submitted on 30 May 2018
- NIPS `Data-Efficient Model-based Reinforcement Learning with Deep Pr…
TMats updated
6 years ago
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Post a reading of your own that uses deep learning for social science analysis and understanding, with a focus on deep reinforcement learning, deep agent based models, or related topics.