Deep RL Bootcamp Lecture 7: SVG, DDPG, and Stochastic Computation Graphs

^ is the square root of epsilon

a simplified version of hard version

a more smooth way to find correct solution

the first term is the REINFORCE term, and the seconde term is our grad log probability of our loss

b is a stochastic node

      

more formula derivations are ignored.

原文地址:https://www.cnblogs.com/ecoflex/p/8977893.html

时间: 2024-08-30 17:08:26

Deep RL Bootcamp Lecture 7: SVG, DDPG, and Stochastic Computation Graphs的相关文章

Deep RL Bootcamp Lecture 2: Sampling-based Approximations and Function Fitting

原文地址:https://www.cnblogs.com/ecoflex/p/8973854.html

Deep RL Bootcamp Lecture 5: Natural Policy Gradients, TRPO, PPO

https://statweb.stanford.edu/~owen/mc/Ch-var-is.pdf https://zhuanlan.zhihu.com/p/29934206 blue curve is the lower bounded one conjugate gradient to solve the optimization problem. Fisher information matrix, natural policy gradient To write down an op

Deep RL Bootcamp Frontiers Lecture I: Recent Advances,

high bias if the robot has learnt something (no changes appear with iterations) however, in the real world tasks, the task could change a little bit, then the robot will failed to generalize. no matter how well we train the robot in situations, there

Deep RL Bootcamp TAs Research Overview

model free: high variance. model based: high bias within 1h of human demonstration of each task, VR!!! 原文地址:https://www.cnblogs.com/ecoflex/p/8990885.html

Tutorials on Inverse Reinforcement Learning

Tutorials on Inverse Reinforcement Learning 2018-07-22 21:44:39 1. Papers:  Inverse Reinforcement Learning: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.394.2178&rep=rep1&type=pdf Cooperative Inverse Reinforcement Learning: http://pape

复现深度强化学习论文经验之谈

近期深度强化学习领域日新月异,其中最酷的一件事情莫过于 OpenAI 和 DeepMind 训练智能体接收人类的反馈而不是传统的奖励信号.本文作者认为复现论文是提升机器学习技能的最好方式之一,所以选择了 OpenAI 论文<Deep Reinforcement Learning from Human Preferences>作为 target,虽获得最后成功,却未实现初衷.如果你也打算复现强化学习论文,那么本文经验也许是你想要的.此外,本文虽对强化学习模型的训练提供了宝贵经验,同时也映射出另外

Introducing Deep Reinforcement

The manuscript of Deep Reinforcement Learning is available now! It makes significant improvements to Deep Reinforcement Learning: An Overview, which has received 100+ citations, by extending its latest version more than one year ago from 70 pages to

深度学习阅读列表 Deep Learning Reading List

Reading List List of reading lists and survey papers: Books Deep Learning, Yoshua Bengio, Ian Goodfellow, Aaron Courville, MIT Press, In preparation. Review Papers Representation Learning: A Review and New Perspectives, Yoshua Bengio, Aaron Courville

Deep Reinforcement Learning for Visual Object Tracking in Videos 论文笔记

Deep Reinforcement Learning for Visual Object Tracking in Videos 论文笔记 arXiv 摘要:本文提出了一种 DRL 算法进行单目标跟踪,算是单目标跟踪中比较早的应用强化学习算法的一个工作.  在基于深度学习的方法中,想学习一个较好的 robust spatial and temporal representation for continuous video data 是非常困难的.  尽管最近的 CNN based tracke