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## Project Request
The project aims to develop a Stock Market Trading Agent using Deep Reinforcement Learning.
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https://arxiv.org/abs/1702.08165
TMats updated
6 years ago
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https://arxiv.org/abs/1707.06203
TMats updated
6 years ago
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## 概要
深層強化学習を用いて文単純化.
モデルはよくあるencoder-decoder attentionモデル.
報酬として,文の単純さ, 文法の正しさ,流暢さ(文の自然さ)の3つの重み付き和を導入.
BLEUなどの自動評価の結果はイマイチだが,人手評価では最も高い評価を得ている.
## 著者
Xingxing Zhang and Mirella Lapata
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논문 리뷰 후보
- [ ] [Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments](http://papers.nips.cc/paper/7217-multi-agent-actor-critic-for-mixed-cooperative-competitive-environments)
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**Describe the use case example you want to see**
Reproduction of classical reinforcement learning paper, Playing Atari with Deep Reinforcement Learning, using SageMaker RL.
**Describe which SageM…
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In this example https://github.com/keras-team/keras-io/blob/master/examples/rl/actor_critic_cartpole.py, the gradient for the actor is defined as the gradient of loss $L = \sum \ln\pi (reward-value)$.…
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# 4. 벨만 방정식: 가치 함수의 재귀적 성질 — 심층강화학습
[https://hiddenbeginner.github.io/Deep-Reinforcement-Learnings/book/Chapter1/4-bellman-equation.html](https://hiddenbeginner.github.io/Deep-Reinforcement-Learnin…
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Hi,
Did you publish any articles about the deep reinforcement learning for robotic grasp?