Model-Based and Model-Free In the previous several posts, we mainly talked about Model-Based Reinforcement Learning. The biggest assumption for Model-Based learning is the whole knowledge of the environment is given, but it is unrealistic in real lif…
Problem of State-Value Function Similar as Policy Iteration in Model-Based Learning, Generalized Policy Iteration will be used in Monte Carlo Control. In Policy Iteration, we keep doing Policy Evaluation and Policy Improvement untill our policy conve…
Introduction to Monte Carlo Tree Search (蒙特卡罗搜索树简介) 部分翻译自“Monte Carlo Tree Search and Its Applications”. 论文链接:http://digitalcommons.morris.umn.edu/cgi/viewcontent.cgi?article=1028&context=horizons MCTS 结合了传统 MC 随机采样的方法 和 树搜索的方法.MC 方法利用重复的随机采样来得到结果.在…
强化学习读书笔记 - 05 - 蒙特卡洛方法(Monte Carlo Methods) 学习笔记: Reinforcement Learning: An Introduction, Richard S. Sutton and Andrew G. Barto c 2014, 2015, 2016 数学符号看不懂的,先看看这里: 强化学习读书笔记 - 00 - 数学符号说明 蒙特卡洛方法简话 蒙特卡洛是一个赌城的名字.冯·诺依曼给这方法起了这个名字,增加其神秘性. 蒙特卡洛方法是一个计算方法,被广泛…
Markus Heikki AnderssonHåkon HelgesenHesselberg Master of Science in Computer Science Submission date: June 2016Supervisor: Helge Langseth, IDI Norwegian University of Science and Technology Department of Computer and Information Science Abstract Thi…
Dictum: Nutrition books in the world. There is no book in life, there is no sunlight; wisdom without books, as if the birds do not have wings. -- Shakespeare 蒙特卡洛(Monte Carlo, MC)方法是一种不基于模型的方法.它不需要具有完备的环境知识,只要求具备经验,即来自于真实的或模拟的环境交互过程中的样本序列\(\{\mathca…
Monte Carlo方法简介(转载) 今天向大家介绍一下我现在主要做的这个东东. Monte Carlo方法又称为随机抽样技巧或统计实验方法,属于计算数学的一个分支,它是在上世纪四十年代中期,为适应当时的曼哈顿计划需求而在美国Los Alamos实验室发展起来的,说白了就是美国为了造原子弹才逼出来的.Monte Carlo方法与一般的计算方法有很大的区别,一般计算方法对解决多维或因素复杂的问题非常困难,而Monte Carlo方法对解决这类问题却比较简单,因此Monte Carlo…
