A summary of the entry resources of deep intensive learning -2016.8_ depth study

Deep Reinforcement Learning Guide:
http://mp.weixin.qq.com/s?__biz=MzI1NTE4NTUwOQ==&mid=2650324914&idx=1&sn= 0baaf404b3d8132243d08b55310de210&scene=2&srcid=062732p5u33rrnikuedslvxn&from=timeline& Isappinstalled=0#wechat_redirect

Detailed in-depth study, build DQN Guide (based on neon framework):
https://mp.weixin.qq.com/s?__biz=MzA3MzI4MjgzMw==&mid=2650716425&idx=1&sn= bf52c653b7cd054ce721ce5be928c623

"Multiagent cooperation and competition with Deep reinforcement Learning" Ardi Tampuu, Tambet Matiisen November 15, is in DeepMind Q -learning based on an extension of the
http://arxiv.org/abs/1511.08779

Deep Reinforcement Learning Guide:
https://mp.weixin.qq.com/s?__biz=MzA3MzI4MjgzMw==&mid=2650716246&idx=2&sn= 2c328097a95839871c8c91c5c5af9de5

"Learning to Optimize"

An application of reinforcement learning, the process of learning optimization added some rewards and punishments strategy, the use of reinforcement learning methods to learn optimization, can be referred to
http://arxiv.org/abs/1606.01885
Read the article:
http://weibo.com/ttarticle/p/show?id=2309403985644224393104

Deep reinforcement Learning depth enhancement of learning resources
https://zhuanlan.zhihu.com/p/20885568

"Dueling network architectures for Deep reinforcement Learning" Google DeepMind; University of Oxford; November 15, cited more than 10 times
http://arxiv.org/abs/1511.06581

Yoshua Bengio Latest thesis: Actor-critic Algorithm for sequence prediction http://t.cn/RtV9tL6
Original: http://arxiv.org/abs/1607.07086
A method of training neural network is proposed to use actor-critic method from reinforcement learning to generate sequences.

In addition: ICML16 reinforcement study related papers 24 articles
http://weibo.com/p/1001603975123651678749