Reinforcement Learning Posts Step-by-step from Markov Property to Markov Decision Process Markov Decision Process in Detail Optimal Value Function and Optimal Policy Dynamic Programming and Policy Evaluation Policy Improvement and Policy Iteration Va…

Reinforcement Learning 对于控制决策问题的解决思路:设计一个回报函数(reward function),如果learning agent(如上面的四足机器人.象棋AI程序)在决定一步后,获得了较好的结果,那么我们给agent一些回报(比如回报函数结果为正),得到较差的结果,那么回报函数为负.比如,四足机器人,如果他向前走了一步(接近目标),那么回报函数为正,后退为负.如果我们能够对每一步进行评价,得到相应的回报函数,那么就好办了,我们只需要找到一条回报值最大的路径(每步的回…

  Deep Learning Research Review Week 2: Reinforcement Learning 转载自: https://adeshpande3.github.io/adeshpande3.github.io/Deep-Learning-Research-Review-Week-2-Reinforcement-Learning This is the 2nd installment of a new series called Deep Learning Resea…

Byte Tank Posts Archive Deep Reinforcement Learning: Playing a Racing Game OCT 6TH, 2016 Agent playing Out Run, session 201609171218_175epsNo time limit, no traffic, 2X time lapse Above is the built deep Q-network (DQN) agent playing Out Run, trained…

Andrej Karpathy blog About Hacker's guide to Neural Networks Deep Reinforcement Learning: Pong from Pixels May 31, 2016 This is a long overdue blog post on Reinforcement Learning (RL). RL is hot! You may have noticed that computers can now automatica…

Active Object Localization with Deep Reinforcement Learning ICCV 2015 最近Deep Reinforcement Learning算是火了一把,在Google Deep Mind的主页上,更是许多关于此的paper,基本都发在ICML,AAAI,IJCAI等各种人工智能,机器学习的牛会顶刊,甚至是Nature,可以参考其官方publication page: https://www.deepmind.com/publicatio…

在机器学习中,我们经常会分类为有监督学习和无监督学习,但是尝尝会忽略一个重要的分支,强化学习.有监督学习和无监督学习非常好去区分,学习的目标,有无标签等都是区分标准.如果说监督学习的目标是预测,那么强化学习就是决策,它通过对周围的环境不断的更新状态,给出奖励或者惩罚的措施,来不断调整并给出新的策略.简单来说,就像小时候你在不该吃零食的时间偷吃了零食,你妈妈知道了会对你做出惩罚,那么下一次就不会犯同样的错误,如果遵守规则,那你妈妈兴许会给你一些奖励,最终的目标都是希望你在该吃饭的时候吃饭,该吃零食…

深度强化学习的18个关键问题 from: https://zhuanlan.zhihu.com/p/32153603 85 人赞了该文章 深度强化学习的问题在哪里?未来怎么走?哪些方面可以突破? 这两天我阅读了两篇篇猛文A Brief Survey of Deep Reinforcement Learning 和 Deep Reinforcement Learning: An Overview ,作者排山倒海的引用了200多篇文献,阐述强化学习未来的方向.原文归纳出深度强化学习中的常见科学问题,…

Hierarchical Object Detection with Deep Reinforcement Learning NIPS 2016 WorkShop  Paper : https://arxiv.org/pdf/1611.03718v1.pdf Project Page : https://github.com/imatge-upc/detection-2016-nipsws  摘要: 我们提出一种基于深度强化学习的等级物体检测方法 (Hierarchical Object  De…

Introduction to Learning to Trade with Reinforcement Learning http://www.wildml.com/2018/02/introduction-to-learning-to-trade-with-reinforcement-learning/ Thanks a lot to @aerinykim, @suzatweet and @hardmaru for the useful feedback! The academic Deep…