Reinforcement Learning（一）：introduction
A little bit probability theory Random Variable 随机变量:未知;它的值取决于随机事件的结果。用大写字母表示随机变量，观察值用小写字母表示，注意，观察值是没有随机性的。 Probability Density Function (PDF) PDF提供了随机变量的值与样本相等的相对可能性，比如下图的高斯分布以及离散分布： 满足以下性质： Expectat
相关文章
- 1. Introduction to Reinforcement Learning
- 2. Reinforcement Learning——Chapter 1 Introduction
- 3. Lecture1: Introduction to Reinforcement Learning
- 4. 强化学习一：Introduction Of Reinforcement Learning
- 5. David Silver《Reinforcement Learning》课程解读—— Lecture 1： Introduction to Reinforcement Learning
- 6. Reinforcement Learning An Introduction~The 10-armed Testbed
- 7. Reinforce learning: Lecture 1 Introduction to Reinforcement Learning 学习笔记
- 8. 1.Introduction of Machine Learning
- 9. Machine Learning(8): Reinforcement learning
- 10. Reinforcement learning and Deep learning
- 更多相关文章...
- • 一对一关联查询 - MyBatis教程
- • MySQL唯一约束（UNIQUE KEY） - MySQL教程
- • RxJava操作符（一）Creating Observables
- • Kotlin学习（一）基本语法
相关标签/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
欢迎关注本站公众号,获取更多信息
相关文章
- 1. Introduction to Reinforcement Learning
- 2. Reinforcement Learning——Chapter 1 Introduction
- 3. Lecture1: Introduction to Reinforcement Learning
- 4. 强化学习一：Introduction Of Reinforcement Learning
- 5. David Silver《Reinforcement Learning》课程解读—— Lecture 1： Introduction to Reinforcement Learning
- 6. Reinforcement Learning An Introduction~The 10-armed Testbed
- 7. Reinforce learning: Lecture 1 Introduction to Reinforcement Learning 学习笔记
- 8. 1.Introduction of Machine Learning
- 9. Machine Learning(8): Reinforcement learning
- 10. Reinforcement learning and Deep learning