- Keras Reinforcement Learning Projects
- Giuseppe Ciaburro
- 127字
- 2021-08-13 15:26:06
Markov chains
A Markov chain is a mathematical model of a random phenomenon that evolves over time in such a way that the past influences the future only through the present. The time can be discrete (a whole variable), continuous (a real variable), or, more generally, a totally ordered whole. In this discussion, only discrete chains are considered. Markov chains were introduced in 1906 by Andrei Andreyevich Markov (1856–1922), from whom the name derives.
The example of a one-dimensional random walk seen in the previous section is a Markov chain; the next value in the chain is a unit that is more or less than the current value with the same probability of occurrence, regardless of the way in which the current value was reached.
推薦閱讀
- 精通MATLAB神經(jīng)網(wǎng)絡(luò)
- 軟件架構(gòu)設(shè)計(jì)
- Visual C# 2008開發(fā)技術(shù)詳解
- 機(jī)器人創(chuàng)新實(shí)訓(xùn)教程
- 自動(dòng)控制理論(非自動(dòng)化專業(yè))
- 塊數(shù)據(jù)5.0:數(shù)據(jù)社會(huì)學(xué)的理論與方法
- ESP8266 Home Automation Projects
- Excel 2007技巧大全
- 大數(shù)據(jù)技術(shù)基礎(chǔ):基于Hadoop與Spark
- 單片機(jī)原理實(shí)用教程
- 從零開始學(xué)JavaScript
- MPC5554/5553微處理器揭秘
- Deep Learning Essentials
- Hands-On Agile Software Development with JIRA
- Containerization with Ansible 2