Optimal Value Function is how much reward the best policy can get from a state s, which is the best senario given state s. It can be defined as: Value Function and Optimal State-Value Function Let's see firstly compare Value Function with Optimal Val…

 > 目  录 <  Agent–Environment Interface Goals and Rewards Returns and Episodes Policies and Value Functions Optimal Policies and Optimal Value Functions  > 笔  记 <  Agent–Environment Interface MDPs are meant to be a straightforward framing of th…

[1] ML Introduction a. supervised learning & unsupervised learning 监督学习:从给定的训练数据集中学习出一个函数(模型参数),当新的数据到来时,可以根据这个函数预测结果.监督学习的训练集要求包括输入输出,也可以说是特征和目标.训练集中的目标是由人标注的.常用于:训练神经网络.决策树.回归分析.统计分类 无监督学习:输入数据没有被标记,也没有确定的结果.样本数据类别未知,需要根据样本间的相似性对样本集进行分类,试图使类内差距最小化,…

Key Concepts in RL 标签(空格分隔): RL_learning OpenAI Spinning Up原址 states and observations (状态和观测) action spaces(动作空间) policies(策略) trajectories(运动轨迹) different formulations of return(不同形式的奖励) the RL optimization problem(RL的优化问题) value functions() States…

A novel massively parallel supercomputer of hundreds of teraOPS-scale includes node architectures based upon System-On-a-Chip technology, i.e., each processing node comprises a single Application Specific Integrated Circuit (ASIC). Within each ASIC n…

factoextra is an R package making easy to extract and visualize the output of exploratory multivariate data analyses, including: Principal Component Analysis (PCA), which is used to summarize the information contained in a continuous (i.e, quantitati…

深度学习课程笔记(七):模仿学习(imitation learning) 2017.12.10 本文所涉及到的 模仿学习,则是从给定的展示中进行学习.机器在这个过程中,也和环境进行交互,但是,并没有显示的得到 reward.在某些任务上,也很难定义 reward.如:自动驾驶,撞死一人,reward为多少,撞到一辆车,reward 为多少,撞到小动物,reward 为多少,撞到 X,reward 又是多少,诸如此类...而某些人类所定义的 reward,可能会造成不可控制的行为,如:我们想让 a…

http://radford.edu/~nokie/classes/360/dp-opt-bst.html Overview Optimal Binary Search Trees - Problem Problem: Sorted set of keys k1,k2,...,knk1,k2,...,kn Key probabilities: p1,p2,...,pnp1,p2,...,pn What tree structure has lowest expected cost? Cost o…

About this Course You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how. Much of this content has never been…

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…